devxpy/glid-3-xl-stable – Run with an API on Replicate

devxpy / glid-3-xl-stable

Stable diffusion, but with more powerful in-painting & out-painting capabilities

Cold

Public
13.4K runs
A100 (80GB)
GitHub
License

Run with an API

Playground API Examples README Versions

Input

prompt

*string

Shift + Return to add a new line

Input prompt

num_inference_steps

integer

(minimum: 1, maximum: 500)

Number of denoising steps.

Default: 50

init_image

file

init image to use

edit_image

file

Preview

The Image you want to edit. If this is provided, then mask is required.

mask

file

Preview

Black and white image to use as mask for inpainting over init_image. White pixels = keep, Black pixels = discard

num_outputs

integer

(minimum: 1, maximum: 4)

Number of images to output

Default: 1

negative_prompt

string

Shift + Return to add a new line

Negative text prompt

outpaint

string

An enumeration.

skip_timesteps

integer

How many diffusion steps to skip

Default: 0

width

integer

Output image width (multiple of 8)

Default: 512

height

integer

Output image height (multiple of 8)

Default: 512

Run this model in Node.js with one line of code:

npx create-replicate --model=devxpy/glid-3-xl-stable

or set up a project from scratch

Install Replicate’s Node.js client library:

npm install replicate

Set the REPLICATE_API_TOKEN environment variable:

export REPLICATE_API_TOKEN=<paste-your-token-here>

Find your API token in your account settings.

Import and set up the client:

import Replicate from "replicate";

const replicate = new Replicate({
  auth: process.env.REPLICATE_API_TOKEN,
});

Run devxpy/glid-3-xl-stable using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

const output = await replicate.run(
  "devxpy/glid-3-xl-stable:7d6a340e1815acf2b3b2ee0fcaf830fbbcd8697e9712ca63d81930c60484d2d7",
  {
    input: {
      mask: "https://replicate.delivery/mgxm/e2dfe2c5-7578-421e-ab55-ae9b553243ec/face_mask.png",
      width: 512,
      height: 512,
      prompt: "Jon snow from the game of thrones",
      outpaint: "expand",
      edit_image: "https://replicate.delivery/mgxm/8a83b0ca-2ea7-4095-8057-499f35a085d8/205032562_345087143808969_4674423480430035886_n.png",
      num_outputs: 1,
      skip_timesteps: 0,
      num_inference_steps: 500
    }
  }
);
console.log(output);

To learn more, take a look at the guide on getting started with Node.js.

Install Replicate’s Python client library:

pip install replicate

Set the REPLICATE_API_TOKEN environment variable:

export REPLICATE_API_TOKEN=<paste-your-token-here>

Find your API token in your account settings.

Import the client:

import replicate

Run devxpy/glid-3-xl-stable using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

output = replicate.run(
    "devxpy/glid-3-xl-stable:7d6a340e1815acf2b3b2ee0fcaf830fbbcd8697e9712ca63d81930c60484d2d7",
    input={
        "mask": "https://replicate.delivery/mgxm/e2dfe2c5-7578-421e-ab55-ae9b553243ec/face_mask.png",
        "width": 512,
        "height": 512,
        "prompt": "Jon snow from the game of thrones",
        "outpaint": "expand",
        "edit_image": "https://replicate.delivery/mgxm/8a83b0ca-2ea7-4095-8057-499f35a085d8/205032562_345087143808969_4674423480430035886_n.png",
        "num_outputs": 1,
        "skip_timesteps": 0,
        "num_inference_steps": 500
    }
)
print(output)

To learn more, take a look at the guide on getting started with Python.

Set the REPLICATE_API_TOKEN environment variable:

export REPLICATE_API_TOKEN=<paste-your-token-here>

Find your API token in your account settings.

Run devxpy/glid-3-xl-stable using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

curl -s -X POST \
  -H "Authorization: Bearer $REPLICATE_API_TOKEN" \
  -H "Content-Type: application/json" \
  -H "Prefer: wait" \
  -d $'{
    "version": "7d6a340e1815acf2b3b2ee0fcaf830fbbcd8697e9712ca63d81930c60484d2d7",
    "input": {
      "mask": "https://replicate.delivery/mgxm/e2dfe2c5-7578-421e-ab55-ae9b553243ec/face_mask.png",
      "width": 512,
      "height": 512,
      "prompt": "Jon snow from the game of thrones",
      "outpaint": "expand",
      "edit_image": "https://replicate.delivery/mgxm/8a83b0ca-2ea7-4095-8057-499f35a085d8/205032562_345087143808969_4674423480430035886_n.png",
      "num_outputs": 1,
      "skip_timesteps": 0,
      "num_inference_steps": 500
    }
  }' \
  https://api.replicate.com/v1/predictions

To learn more, take a look at Replicate’s HTTP API reference docs.

Output

{
  "completed_at": "2022-10-10T19:35:56.409213Z",
  "created_at": "2022-10-10T19:34:28.966972Z",
  "data_removed": false,
  "error": null,
  "id": "thh6qyqtmjbd5adxy7w5s3pfhy",
  "input": {
    "mask": "https://replicate.delivery/mgxm/e2dfe2c5-7578-421e-ab55-ae9b553243ec/face_mask.png",
    "prompt": "Jon snow from the game of thrones",
    "edit_image": "https://replicate.delivery/mgxm/8a83b0ca-2ea7-4095-8057-499f35a085d8/205032562_345087143808969_4674423480430035886_n.png",
    "num_outputs": 1,
    "num_inference_steps": "500"
  },
  "logs": "$ /root/.pyenv/versions/3.10.7/bin/python sample.py --model_path inpaint.pt --edit /tmp/tmpc_o91y0t205032562_345087143808969_4674423480430035886_n.png --mask /tmp/tmpvkqeu1cpface_mask.png --steps 500 --text Jon snow from the game of thrones --num_batches 1\nUsing device: cuda:0\nmaking attention of type 'vanilla' with 512 in_channels\nWorking with z of shape (1, 4, 32, 32) = 4096 dimensions.\nmaking attention of type 'vanilla' with 512 in_channels\nSome weights of the model checkpoint at openai/clip-vit-large-patch14 were not used when initializing CLIPTextModel: ['vision_model.encoder.layers.19.self_attn.k_proj.bias', 'vision_model.encoder.layers.21.layer_norm1.weight', 'vision_model.encoder.layers.0.self_attn.out_proj.bias', 'vision_model.encoder.layers.14.layer_norm1.bias', 'vision_model.encoder.layers.21.mlp.fc2.weight', 'vision_model.encoder.layers.3.mlp.fc1.bias', 'vision_model.encoder.layers.11.mlp.fc1.weight', 'vision_model.encoder.layers.3.self_attn.v_proj.bias', 'vision_model.encoder.layers.10.mlp.fc2.weight', 'vision_model.encoder.layers.8.self_attn.q_proj.bias', 'vision_model.encoder.layers.6.layer_norm1.bias', 'vision_model.encoder.layers.18.self_attn.k_proj.bias', 'vision_model.encoder.layers.8.layer_norm2.bias', 'vision_model.encoder.layers.20.mlp.fc1.bias', 'vision_model.encoder.layers.2.layer_norm1.bias', 'vision_model.encoder.layers.17.self_attn.v_proj.bias', 'vision_model.encoder.layers.1.self_attn.q_proj.bias', 'vision_model.encoder.layers.8.mlp.fc1.weight', 'vision_model.encoder.layers.13.layer_norm1.bias', 'vision_model.encoder.layers.21.self_attn.q_proj.weight', 'vision_model.encoder.layers.13.self_attn.k_proj.bias', 'vision_model.encoder.layers.10.self_attn.v_proj.bias', 'vision_model.encoder.layers.6.layer_norm2.weight', 'vision_model.encoder.layers.11.layer_norm2.weight', 'vision_model.encoder.layers.18.mlp.fc2.weight', 'vision_model.encoder.layers.8.layer_norm1.bias', 'vision_model.encoder.layers.4.mlp.fc2.weight', 'vision_model.encoder.layers.2.self_attn.out_proj.weight', 'vision_model.encoder.layers.8.mlp.fc1.bias', 'vision_model.encoder.layers.11.mlp.fc2.bias', 'vision_model.encoder.layers.17.layer_norm1.bias', 'vision_model.encoder.layers.2.layer_norm2.weight', 'vision_model.embeddings.position_ids', 'vision_model.encoder.layers.2.mlp.fc1.weight', 'vision_model.encoder.layers.20.self_attn.v_proj.bias', 'vision_model.encoder.layers.17.layer_norm2.bias', 'vision_model.encoder.layers.4.self_attn.out_proj.weight', 'vision_model.encoder.layers.4.self_attn.v_proj.weight', 'vision_model.encoder.layers.17.self_attn.q_proj.weight', 'vision_model.encoder.layers.20.self_attn.v_proj.weight', 'vision_model.encoder.layers.7.mlp.fc2.weight', 'vision_model.encoder.layers.3.layer_norm1.weight', 'vision_model.encoder.layers.22.self_attn.v_proj.weight', 'vision_model.encoder.layers.21.layer_norm1.bias', 'vision_model.encoder.layers.2.mlp.fc2.bias', 'vision_model.encoder.layers.4.self_attn.q_proj.bias', 'vision_model.encoder.layers.6.self_attn.k_proj.weight', 'vision_model.encoder.layers.6.layer_norm2.bias', 'vision_model.encoder.layers.11.mlp.fc2.weight', 'vision_model.encoder.layers.15.mlp.fc1.bias', 'vision_model.encoder.layers.15.layer_norm2.weight', 'vision_model.encoder.layers.4.self_attn.k_proj.weight', 'vision_model.encoder.layers.9.self_attn.v_proj.weight', 'vision_model.encoder.layers.16.self_attn.q_proj.weight', 'vision_model.encoder.layers.10.layer_norm1.bias', 'vision_model.encoder.layers.9.self_attn.k_proj.bias', 'vision_model.encoder.layers.7.self_attn.q_proj.weight', 'vision_model.encoder.layers.13.self_attn.q_proj.bias', 'vision_model.encoder.layers.5.layer_norm2.bias', 'vision_model.encoder.layers.15.self_attn.q_proj.weight', 'vision_model.encoder.layers.15.mlp.fc1.weight', 'vision_model.encoder.layers.21.self_attn.out_proj.weight', 'vision_model.encoder.layers.13.self_attn.q_proj.weight', 'vision_model.encoder.layers.19.self_attn.q_proj.weight', 'vision_model.encoder.layers.17.self_attn.out_proj.weight', 'vision_model.encoder.layers.10.self_attn.out_proj.bias', 'vision_model.encoder.layers.19.mlp.fc2.weight', 'vision_model.encoder.layers.13.self_attn.out_proj.bias', 'vision_model.encoder.layers.16.mlp.fc2.weight', 'vision_model.encoder.layers.3.mlp.fc1.weight', 'vision_model.encoder.layers.4.mlp.fc1.bias', 'vision_model.encoder.layers.0.mlp.fc2.bias', 'vision_model.encoder.layers.21.mlp.fc2.bias', 'vision_model.encoder.layers.18.layer_norm2.bias', 'vision_model.encoder.layers.23.mlp.fc2.bias', 'vision_model.encoder.layers.8.mlp.fc2.bias', 'vision_model.encoder.layers.21.self_attn.k_proj.weight', 'vision_model.encoder.layers.7.mlp.fc1.bias', 'vision_model.encoder.layers.19.layer_norm1.weight', 'vision_model.encoder.layers.0.layer_norm1.weight', 'vision_model.encoder.layers.4.mlp.fc1.weight', 'vision_model.encoder.layers.16.self_attn.q_proj.bias', 'vision_model.encoder.layers.1.layer_norm2.bias', 'vision_model.encoder.layers.20.layer_norm2.bias', 'vision_model.encoder.layers.12.self_attn.k_proj.bias', 'vision_model.encoder.layers.4.layer_norm1.weight', 'vision_model.encoder.layers.20.self_attn.q_proj.bias', 'vision_model.encoder.layers.6.self_attn.q_proj.bias', 'vision_model.encoder.layers.3.layer_norm2.weight', 'vision_model.encoder.layers.4.self_attn.k_proj.bias', 'vision_model.encoder.layers.5.self_attn.out_proj.bias', 'vision_model.encoder.layers.10.mlp.fc1.weight', 'vision_model.encoder.layers.17.self_attn.out_proj.bias', 'vision_model.encoder.layers.5.layer_norm1.weight', 'vision_model.encoder.layers.7.mlp.fc1.weight', 'vision_model.encoder.layers.2.self_attn.q_proj.weight', 'vision_model.encoder.layers.7.layer_norm2.bias', 'vision_model.encoder.layers.0.mlp.fc1.bias', 'vision_model.encoder.layers.8.self_attn.v_proj.weight', 'text_projection.weight', 'vision_model.encoder.layers.6.mlp.fc1.weight', 'vision_model.encoder.layers.20.layer_norm1.weight', 'vision_model.encoder.layers.21.self_attn.v_proj.weight', 'vision_model.encoder.layers.8.self_attn.k_proj.weight', 'vision_model.encoder.layers.13.self_attn.v_proj.bias', 'vision_model.encoder.layers.8.self_attn.out_proj.weight', 'vision_model.encoder.layers.13.self_attn.k_proj.weight', 'vision_model.encoder.layers.8.self_attn.out_proj.bias', 'vision_model.encoder.layers.12.layer_norm1.bias', 'vision_model.encoder.layers.7.self_attn.out_proj.bias', 'vision_model.encoder.layers.20.layer_norm1.bias', 'vision_model.encoder.layers.15.self_attn.k_proj.weight', 'vision_model.encoder.layers.22.mlp.fc1.weight', 'vision_model.encoder.layers.11.self_attn.q_proj.weight', 'vision_model.encoder.layers.1.self_attn.k_proj.bias', 'vision_model.encoder.layers.14.self_attn.k_proj.weight', 'vision_model.encoder.layers.22.self_attn.k_proj.bias', 'vision_model.encoder.layers.3.self_attn.q_proj.bias', 'vision_model.encoder.layers.12.mlp.fc1.bias', 'vision_model.encoder.layers.8.layer_norm2.weight', 'vision_model.encoder.layers.19.self_attn.k_proj.weight', 'vision_model.encoder.layers.17.layer_norm1.weight', 'vision_model.encoder.layers.17.self_attn.k_proj.weight', 'vision_model.encoder.layers.13.layer_norm1.weight', 'vision_model.encoder.layers.22.self_attn.out_proj.bias', 'vision_model.encoder.layers.8.self_attn.k_proj.bias', 'vision_model.encoder.layers.10.self_attn.k_proj.bias', 'vision_model.encoder.layers.18.self_attn.v_proj.weight', 'vision_model.encoder.layers.18.self_attn.out_proj.bias', 'vision_model.encoder.layers.15.layer_norm1.weight', 'vision_model.encoder.layers.13.mlp.fc2.bias', 'vision_model.encoder.layers.23.layer_norm1.bias', 'vision_model.encoder.layers.7.self_attn.q_proj.bias', 'vision_model.encoder.layers.18.layer_norm1.bias', 'vision_model.encoder.layers.23.mlp.fc1.weight', 'vision_model.encoder.layers.16.self_attn.v_proj.weight', 'vision_model.encoder.layers.20.self_attn.k_proj.weight', 'vision_model.encoder.layers.11.self_attn.v_proj.bias', 'vision_model.encoder.layers.19.mlp.fc2.bias', 'vision_model.encoder.layers.13.mlp.fc1.bias', 'vision_model.encoder.layers.3.self_attn.out_proj.bias', 'vision_model.encoder.layers.3.mlp.fc2.bias', 'vision_model.encoder.layers.2.self_attn.v_proj.weight', 'vision_model.encoder.layers.5.mlp.fc1.bias', 'vision_model.encoder.layers.5.mlp.fc2.bias', 'vision_model.encoder.layers.1.mlp.fc2.bias', 'vision_model.encoder.layers.19.layer_norm2.bias', 'vision_model.encoder.layers.15.layer_norm1.bias', 'vision_model.encoder.layers.16.self_attn.k_proj.bias', 'vision_model.encoder.layers.3.self_attn.k_proj.weight', 'vision_model.encoder.layers.3.layer_norm2.bias', 'vision_model.encoder.layers.18.mlp.fc1.bias', 'vision_model.encoder.layers.7.layer_norm2.weight', 'vision_model.encoder.layers.2.self_attn.v_proj.bias', 'vision_model.encoder.layers.3.self_attn.k_proj.bias', 'vision_model.encoder.layers.0.self_attn.v_proj.weight', 'vision_model.encoder.layers.0.self_attn.q_proj.bias', 'vision_model.encoder.layers.12.self_attn.v_proj.bias', 'vision_model.encoder.layers.14.layer_norm1.weight', 'vision_model.encoder.layers.4.layer_norm2.bias', 'vision_model.encoder.layers.20.self_attn.out_proj.bias', 'vision_model.encoder.layers.12.self_attn.out_proj.bias', 'vision_model.encoder.layers.6.mlp.fc2.weight', 'vision_model.encoder.layers.21.self_attn.out_proj.bias', 'vision_model.encoder.layers.22.mlp.fc2.bias', 'vision_model.encoder.layers.18.mlp.fc2.bias', 'vision_model.embeddings.patch_embedding.weight', 'vision_model.encoder.layers.9.self_attn.v_proj.bias', 'vision_model.encoder.layers.13.self_attn.v_proj.weight', 'vision_model.encoder.layers.9.layer_norm2.weight', 'vision_model.encoder.layers.10.layer_norm2.bias', 'vision_model.encoder.layers.22.layer_norm2.bias', 'vision_model.encoder.layers.22.layer_norm2.weight', 'vision_model.encoder.layers.0.self_attn.k_proj.bias', 'vision_model.encoder.layers.0.self_attn.k_proj.weight', 'vision_model.encoder.layers.7.self_attn.v_proj.weight', 'vision_model.encoder.layers.3.self_attn.q_proj.weight', 'vision_model.encoder.layers.16.self_attn.v_proj.bias', 'vision_model.encoder.layers.23.self_attn.out_proj.weight', 'vision_model.encoder.layers.10.self_attn.out_proj.weight', 'vision_model.encoder.layers.14.self_attn.v_proj.bias', 'vision_model.encoder.layers.4.mlp.fc2.bias', 'vision_model.encoder.layers.11.self_attn.v_proj.weight', 'vision_model.encoder.layers.12.mlp.fc2.weight', 'vision_model.encoder.layers.7.self_attn.v_proj.bias', 'vision_model.encoder.layers.1.self_attn.q_proj.weight', 'vision_model.encoder.layers.19.layer_norm2.weight', 'vision_model.encoder.layers.21.layer_norm2.bias', 'vision_model.encoder.layers.2.self_attn.k_proj.weight', 'vision_model.encoder.layers.18.self_attn.k_proj.weight', 'vision_model.encoder.layers.13.self_attn.out_proj.weight', 'vision_model.encoder.layers.21.self_attn.q_proj.bias', 'vision_model.encoder.layers.20.self_attn.out_proj.weight', 'vision_model.encoder.layers.16.self_attn.k_proj.weight', 'vision_model.encoder.layers.6.self_attn.v_proj.weight', 'vision_model.encoder.layers.11.self_attn.out_proj.weight', 'vision_model.encoder.layers.2.layer_norm1.weight', 'vision_model.encoder.layers.7.layer_norm1.bias', 'vision_model.encoder.layers.14.self_attn.v_proj.weight', 'vision_model.encoder.layers.16.layer_norm1.bias', 'vision_model.encoder.layers.15.layer_norm2.bias', 'vision_model.encoder.layers.16.mlp.fc1.bias', 'vision_model.encoder.layers.20.mlp.fc2.bias', 'vision_model.encoder.layers.23.self_attn.v_proj.bias', 'vision_model.encoder.layers.3.mlp.fc2.weight', 'vision_model.encoder.layers.23.layer_norm2.weight', 'vision_model.encoder.layers.20.self_attn.k_proj.bias', 'vision_model.encoder.layers.6.layer_norm1.weight', 'vision_model.encoder.layers.1.self_attn.out_proj.bias', 'vision_model.encoder.layers.6.mlp.fc2.bias', 'vision_model.encoder.layers.22.self_attn.q_proj.bias', 'vision_model.encoder.layers.9.mlp.fc2.bias', 'vision_model.encoder.layers.7.mlp.fc2.bias', 'vision_model.encoder.layers.23.layer_norm1.weight', 'vision_model.encoder.layers.6.self_attn.v_proj.bias', 'vision_model.encoder.layers.4.self_attn.out_proj.bias', 'vision_model.encoder.layers.21.layer_norm2.weight', 'vision_model.encoder.layers.2.mlp.fc2.weight', 'vision_model.encoder.layers.0.self_attn.out_proj.weight', 'vision_model.encoder.layers.6.self_attn.k_proj.bias', 'vision_model.encoder.layers.22.mlp.fc2.weight', 'vision_model.embeddings.position_embedding.weight', 'vision_model.encoder.layers.15.mlp.fc2.weight', 'vision_model.encoder.layers.3.layer_norm1.bias', 'vision_model.encoder.layers.5.self_attn.v_proj.weight', 'vision_model.encoder.layers.10.mlp.fc1.bias', 'vision_model.encoder.layers.2.layer_norm2.bias', 'vision_model.encoder.layers.16.self_attn.out_proj.bias', 'vision_model.encoder.layers.21.mlp.fc1.bias', 'vision_model.encoder.layers.6.self_attn.out_proj.weight', 'vision_model.encoder.layers.6.self_attn.q_proj.weight', 'vision_model.encoder.layers.5.layer_norm1.bias', 'vision_model.encoder.layers.10.layer_norm1.weight', 'vision_model.encoder.layers.13.layer_norm2.bias', 'vision_model.encoder.layers.23.self_attn.q_proj.weight', 'vision_model.encoder.layers.7.self_attn.out_proj.weight', 'vision_model.encoder.layers.11.self_attn.q_proj.bias', 'vision_model.encoder.layers.5.layer_norm2.weight', 'vision_model.encoder.layers.16.layer_norm2.bias', 'vision_model.encoder.layers.16.layer_norm2.weight', 'vision_model.encoder.layers.10.self_attn.q_proj.bias', 'vision_model.encoder.layers.0.layer_norm2.weight', 'vision_model.encoder.layers.12.self_attn.q_proj.bias', 'vision_model.encoder.layers.11.self_attn.k_proj.bias', 'vision_model.encoder.layers.7.layer_norm1.weight', 'vision_model.encoder.layers.7.self_attn.k_proj.bias', 'vision_model.encoder.layers.11.layer_norm2.bias', 'vision_model.encoder.layers.21.self_attn.k_proj.bias', 'vision_model.encoder.layers.21.self_attn.v_proj.bias', 'vision_model.encoder.layers.9.self_attn.q_proj.bias', 'vision_model.encoder.layers.15.self_attn.v_proj.weight', 'vision_model.encoder.layers.10.self_attn.q_proj.weight', 'vision_model.encoder.layers.6.self_attn.out_proj.bias', 'vision_model.encoder.layers.20.layer_norm2.weight', 'vision_model.encoder.layers.2.self_attn.k_proj.bias', 'vision_model.pre_layrnorm.weight', 'vision_model.encoder.layers.18.self_attn.out_proj.weight', 'vision_model.encoder.layers.19.mlp.fc1.weight', 'vision_model.encoder.layers.13.mlp.fc2.weight', 'vision_model.encoder.layers.22.self_attn.k_proj.weight', 'vision_model.encoder.layers.17.mlp.fc2.bias', 'vision_model.encoder.layers.23.mlp.fc1.bias', 'vision_model.encoder.layers.7.self_attn.k_proj.weight', 'vision_model.encoder.layers.11.mlp.fc1.bias', 'vision_model.encoder.layers.10.layer_norm2.weight', 'vision_model.encoder.layers.21.mlp.fc1.weight', 'vision_model.encoder.layers.14.self_attn.q_proj.bias', 'vision_model.encoder.layers.5.self_attn.q_proj.bias', 'vision_model.encoder.layers.1.self_attn.out_proj.weight', 'vision_model.encoder.layers.14.mlp.fc1.bias', 'vision_model.encoder.layers.17.self_attn.q_proj.bias', 'vision_model.encoder.layers.14.self_attn.q_proj.weight', 'vision_model.encoder.layers.12.layer_norm1.weight', 'vision_model.encoder.layers.18.self_attn.q_proj.weight', 'vision_model.encoder.layers.15.self_attn.v_proj.bias', 'vision_model.encoder.layers.2.mlp.fc1.bias', 'vision_model.pre_layrnorm.bias', 'vision_model.encoder.layers.23.self_attn.k_proj.weight', 'vision_model.encoder.layers.14.self_attn.out_proj.weight', 'vision_model.encoder.layers.8.self_attn.q_proj.weight', 'vision_model.encoder.layers.10.mlp.fc2.bias', 'vision_model.encoder.layers.17.mlp.fc2.weight', 'vision_model.encoder.layers.8.layer_norm1.weight', 'vision_model.encoder.layers.11.self_attn.k_proj.weight', 'vision_model.encoder.layers.15.self_attn.out_proj.weight', 'vision_model.encoder.layers.8.mlp.fc2.weight', 'vision_model.encoder.layers.19.layer_norm1.bias', 'vision_model.encoder.layers.8.self_attn.v_proj.bias', 'vision_model.encoder.layers.22.self_attn.q_proj.weight', 'vision_model.encoder.layers.23.self_attn.k_proj.bias', 'vision_model.encoder.layers.0.mlp.fc1.weight', 'vision_model.encoder.layers.16.layer_norm1.weight', 'vision_model.encoder.layers.18.layer_norm1.weight', 'vision_model.encoder.layers.2.self_attn.out_proj.bias', 'vision_model.encoder.layers.9.self_attn.q_proj.weight', 'vision_model.encoder.layers.15.self_attn.q_proj.bias', 'vision_model.encoder.layers.17.self_attn.v_proj.weight', 'vision_model.encoder.layers.14.layer_norm2.bias', 'vision_model.encoder.layers.14.self_attn.out_proj.bias', 'vision_model.encoder.layers.1.self_attn.k_proj.weight', 'vision_model.encoder.layers.11.self_attn.out_proj.bias', 'vision_model.encoder.layers.12.self_attn.out_proj.weight', 'vision_model.encoder.layers.20.mlp.fc2.weight', 'vision_model.encoder.layers.9.mlp.fc2.weight', 'vision_model.encoder.layers.23.mlp.fc2.weight', 'vision_model.encoder.layers.5.self_attn.q_proj.weight', 'vision_model.encoder.layers.0.self_attn.v_proj.bias', 'vision_model.encoder.layers.4.layer_norm1.bias', 'vision_model.encoder.layers.17.mlp.fc1.bias', 'vision_model.encoder.layers.20.mlp.fc1.weight', 'vision_model.encoder.layers.5.mlp.fc2.weight', 'vision_model.encoder.layers.23.self_attn.q_proj.bias', 'vision_model.encoder.layers.11.layer_norm1.weight', 'vision_model.encoder.layers.1.mlp.fc1.bias', 'vision_model.encoder.layers.10.self_attn.k_proj.weight', 'vision_model.encoder.layers.1.self_attn.v_proj.weight', 'vision_model.encoder.layers.0.self_attn.q_proj.weight', 'vision_model.encoder.layers.23.self_attn.out_proj.bias', 'vision_model.encoder.layers.22.layer_norm1.bias', 'vision_model.encoder.layers.14.layer_norm2.weight', 'vision_model.encoder.layers.15.self_attn.k_proj.bias', 'vision_model.encoder.layers.13.layer_norm2.weight', 'vision_model.encoder.layers.9.layer_norm1.bias', 'vision_model.encoder.layers.20.self_attn.q_proj.weight', 'vision_model.encoder.layers.6.mlp.fc1.bias', 'vision_model.encoder.layers.9.self_attn.k_proj.weight', 'vision_model.encoder.layers.17.layer_norm2.weight', 'vision_model.encoder.layers.18.self_attn.v_proj.bias', 'vision_model.encoder.layers.4.self_attn.v_proj.bias', 'vision_model.encoder.layers.3.self_attn.v_proj.weight', 'vision_model.encoder.layers.9.self_attn.out_proj.bias', 'vision_model.encoder.layers.19.self_attn.v_proj.weight', 'vision_model.encoder.layers.9.mlp.fc1.bias', 'vision_model.encoder.layers.1.layer_norm2.weight', 'vision_model.encoder.layers.16.self_attn.out_proj.weight', 'vision_model.encoder.layers.19.self_attn.q_proj.bias', 'vision_model.encoder.layers.0.layer_norm2.bias', 'vision_model.encoder.layers.5.self_attn.out_proj.weight', 'vision_model.encoder.layers.15.self_attn.out_proj.bias', 'vision_model.encoder.layers.12.layer_norm2.bias', 'vision_model.encoder.layers.9.layer_norm2.bias', 'vision_model.encoder.layers.1.layer_norm1.bias', 'vision_model.encoder.layers.22.mlp.fc1.bias', 'vision_model.encoder.layers.14.mlp.fc1.weight', 'vision_model.encoder.layers.13.mlp.fc1.weight', 'vision_model.encoder.layers.5.mlp.fc1.weight', 'vision_model.encoder.layers.10.self_attn.v_proj.weight', 'visual_projection.weight', 'vision_model.encoder.layers.1.mlp.fc2.weight', 'vision_model.post_layernorm.bias', 'vision_model.encoder.layers.3.self_attn.out_proj.weight', 'vision_model.embeddings.class_embedding', 'vision_model.encoder.layers.5.self_attn.v_proj.bias', 'vision_model.encoder.layers.18.layer_norm2.weight', 'vision_model.encoder.layers.0.layer_norm1.bias', 'vision_model.encoder.layers.1.self_attn.v_proj.bias', 'vision_model.encoder.layers.22.self_attn.v_proj.bias', 'vision_model.encoder.layers.23.self_attn.v_proj.weight', 'vision_model.encoder.layers.12.mlp.fc1.weight', 'vision_model.encoder.layers.19.mlp.fc1.bias', 'vision_model.encoder.layers.22.self_attn.out_proj.weight', 'vision_model.encoder.layers.5.self_attn.k_proj.weight', 'vision_model.encoder.layers.12.self_attn.v_proj.weight', 'vision_model.encoder.layers.1.layer_norm1.weight', 'vision_model.encoder.layers.4.self_attn.q_proj.weight', 'vision_model.encoder.layers.12.self_attn.q_proj.weight', 'vision_model.encoder.layers.9.layer_norm1.weight', 'vision_model.encoder.layers.15.mlp.fc2.bias', 'vision_model.encoder.layers.16.mlp.fc2.bias', 'vision_model.encoder.layers.14.mlp.fc2.bias', 'vision_model.encoder.layers.19.self_attn.v_proj.bias', 'vision_model.encoder.layers.2.self_attn.q_proj.bias', 'vision_model.encoder.layers.5.self_attn.k_proj.bias', 'vision_model.encoder.layers.12.self_attn.k_proj.weight', 'vision_model.encoder.layers.19.self_attn.out_proj.weight', 'vision_model.encoder.layers.19.self_attn.out_proj.bias', 'vision_model.encoder.layers.4.layer_norm2.weight', 'vision_model.encoder.layers.14.mlp.fc2.weight', 'vision_model.encoder.layers.12.mlp.fc2.bias', 'vision_model.post_layernorm.weight', 'vision_model.encoder.layers.0.mlp.fc2.weight', 'vision_model.encoder.layers.14.self_attn.k_proj.bias', 'vision_model.encoder.layers.1.mlp.fc1.weight', 'vision_model.encoder.layers.22.layer_norm1.weight', 'vision_model.encoder.layers.17.mlp.fc1.weight', 'vision_model.encoder.layers.9.mlp.fc1.weight', 'logit_scale', 'vision_model.encoder.layers.12.layer_norm2.weight', 'vision_model.encoder.layers.9.self_attn.out_proj.weight', 'vision_model.encoder.layers.11.layer_norm1.bias', 'vision_model.encoder.layers.16.mlp.fc1.weight', 'vision_model.encoder.layers.18.self_attn.q_proj.bias', 'vision_model.encoder.layers.23.layer_norm2.bias', 'vision_model.encoder.layers.17.self_attn.k_proj.bias', 'vision_model.encoder.layers.18.mlp.fc1.weight']\n- This IS expected if you are initializing CLIPTextModel from the checkpoint of a model trained on another task or with another architecture (e.g. initializing a BertForSequenceClassification model from a BertForPreTraining model).\n- This IS NOT expected if you are initializing CLIPTextModel from the checkpoint of a model that you expect to be exactly identical (initializing a BertForSequenceClassification model from a BertForSequenceClassification model).\n/src/sample.py:354: DeprecationWarning: ANTIALIAS is deprecated and will be removed in Pillow 10 (2023-07-01). Use Resampling.LANCZOS instead.\n  mask_image = mask_image.resize((input_image.shape[3],input_image.shape[2]), Image.ANTIALIAS)\n\n  0%|          | 0/500 [00:00<?, ?it/s]\n  0%|          | 1/500 [00:00<05:47,  1.44it/s]\n  0%|          | 2/500 [00:01<04:35,  1.80it/s]\n  1%|          | 3/500 [00:01<04:13,  1.96it/s]\n  1%|          | 4/500 [00:01<02:55,  2.83it/s]\n  1%|          | 5/500 [00:01<02:12,  3.74it/s]\n  1%|          | 6/500 [00:01<01:46,  4.65it/s]\n  1%|▏         | 7/500 [00:02<01:29,  5.49it/s]\n  2%|▏         | 8/500 [00:02<01:19,  6.23it/s]\n  2%|▏         | 9/500 [00:02<01:11,  6.83it/s]\n  2%|▏         | 10/500 [00:02<01:06,  7.34it/s]\n  2%|▏         | 11/500 [00:02<01:03,  7.73it/s]\n  2%|▏         | 12/500 [00:02<01:00,  8.03it/s]\n  3%|▎         | 13/500 [00:02<00:59,  8.24it/s]\n  3%|▎         | 14/500 [00:02<00:57,  8.40it/s]\n  3%|▎         | 15/500 [00:02<00:56,  8.51it/s]\n  3%|▎         | 16/500 [00:03<00:56,  8.59it/s]\n  3%|▎         | 17/500 [00:03<00:55,  8.65it/s]\n  4%|▎         | 18/500 [00:03<00:55,  8.69it/s]\n  4%|▍         | 19/500 [00:03<00:55,  8.69it/s]\n  4%|▍         | 20/500 [00:03<00:55,  8.70it/s]\n  4%|▍         | 21/500 [00:03<00:54,  8.73it/s]\n  4%|▍         | 22/500 [00:03<00:54,  8.75it/s]\n  5%|▍         | 23/500 [00:03<00:54,  8.76it/s]\n  5%|▍         | 24/500 [00:04<00:54,  8.78it/s]\n  5%|▌         | 25/500 [00:04<00:53,  8.80it/s]\n  5%|▌         | 26/500 [00:04<01:26,  5.48it/s]\n  5%|▌         | 27/500 [00:04<01:16,  6.17it/s]\n  6%|▌         | 28/500 [00:04<01:09,  6.77it/s]\n  6%|▌         | 29/500 [00:04<01:04,  7.28it/s]\n  6%|▌         | 30/500 [00:04<01:01,  7.68it/s]\n  6%|▌         | 31/500 [00:05<00:58,  7.99it/s]\n  6%|▋         | 32/500 [00:05<00:56,  8.21it/s]\n  7%|▋         | 33/500 [00:05<00:55,  8.39it/s]\n  7%|▋         | 34/500 [00:05<00:54,  8.51it/s]\n  7%|▋         | 35/500 [00:05<00:54,  8.60it/s]\n  7%|▋         | 36/500 [00:05<00:53,  8.65it/s]\n  7%|▋         | 37/500 [00:05<00:53,  8.70it/s]\n  8%|▊         | 38/500 [00:05<00:53,  8.69it/s]\n  8%|▊         | 39/500 [00:05<00:52,  8.70it/s]\n  8%|▊         | 40/500 [00:06<00:52,  8.73it/s]\n  8%|▊         | 41/500 [00:06<00:52,  8.76it/s]\n  8%|▊         | 42/500 [00:06<00:52,  8.76it/s]\n  9%|▊         | 43/500 [00:06<00:52,  8.77it/s]\n  9%|▉         | 44/500 [00:06<00:52,  8.77it/s]\n  9%|▉         | 45/500 [00:06<00:51,  8.76it/s]\n  9%|▉         | 46/500 [00:06<00:51,  8.78it/s]\n  9%|▉         | 47/500 [00:06<00:51,  8.80it/s]\n 10%|▉         | 48/500 [00:06<00:51,  8.74it/s]\n 10%|▉         | 49/500 [00:07<00:51,  8.74it/s]\n 10%|█         | 50/500 [00:07<00:51,  8.75it/s]\n 10%|█         | 51/500 [00:07<01:21,  5.54it/s]\n 10%|█         | 52/500 [00:07<01:12,  6.22it/s]\n 11%|█         | 53/500 [00:07<01:05,  6.81it/s]\n 11%|█         | 54/500 [00:07<01:01,  7.30it/s]\n 11%|█         | 55/500 [00:07<00:57,  7.70it/s]\n 11%|█         | 56/500 [00:08<00:55,  7.98it/s]\n 11%|█▏        | 57/500 [00:08<00:54,  8.20it/s]\n 12%|█▏        | 58/500 [00:08<00:52,  8.39it/s]\n 12%|█▏        | 59/500 [00:08<00:51,  8.49it/s]\n 12%|█▏        | 60/500 [00:08<00:51,  8.59it/s]\n 12%|█▏        | 61/500 [00:08<00:50,  8.65it/s]\n 12%|█▏        | 62/500 [00:08<00:50,  8.70it/s]\n 13%|█▎        | 63/500 [00:08<00:50,  8.74it/s]\n 13%|█▎        | 64/500 [00:09<00:49,  8.75it/s]\n 13%|█▎        | 65/500 [00:09<00:49,  8.77it/s]\n 13%|█▎        | 66/500 [00:09<00:49,  8.78it/s]\n 13%|█▎        | 67/500 [00:09<00:49,  8.75it/s]\n 14%|█▎        | 68/500 [00:09<00:49,  8.75it/s]\n 14%|█▍        | 69/500 [00:09<00:49,  8.75it/s]\n 14%|█▍        | 70/500 [00:09<00:49,  8.75it/s]\n 14%|█▍        | 71/500 [00:09<00:49,  8.75it/s]\n 14%|█▍        | 72/500 [00:09<00:48,  8.77it/s]\n 15%|█▍        | 73/500 [00:10<00:48,  8.79it/s]\n 15%|█▍        | 74/500 [00:10<00:48,  8.80it/s]\n 15%|█▌        | 75/500 [00:10<00:48,  8.78it/s]\n 15%|█▌        | 76/500 [00:10<01:16,  5.53it/s]\n 15%|█▌        | 77/500 [00:10<01:08,  6.21it/s]\n 16%|█▌        | 78/500 [00:10<01:01,  6.81it/s]\n 16%|█▌        | 79/500 [00:10<00:57,  7.31it/s]\n 16%|█▌        | 80/500 [00:11<00:54,  7.71it/s]\n 16%|█▌        | 81/500 [00:11<00:52,  8.00it/s]\n 16%|█▋        | 82/500 [00:11<00:50,  8.22it/s]\n 17%|█▋        | 83/500 [00:11<00:49,  8.37it/s]\n 17%|█▋        | 84/500 [00:11<00:49,  8.49it/s]\n 17%|█▋        | 85/500 [00:11<00:48,  8.56it/s]\n 17%|█▋        | 86/500 [00:11<00:48,  8.61it/s]\n 17%|█▋        | 87/500 [00:11<00:47,  8.65it/s]\n 18%|█▊        | 88/500 [00:11<00:47,  8.69it/s]\n 18%|█▊        | 89/500 [00:12<00:47,  8.71it/s]\n 18%|█▊        | 90/500 [00:12<00:46,  8.74it/s]\n 18%|█▊        | 91/500 [00:12<00:46,  8.74it/s]\n 18%|█▊        | 92/500 [00:12<00:46,  8.75it/s]\n 19%|█▊        | 93/500 [00:12<00:46,  8.75it/s]\n 19%|█▉        | 94/500 [00:12<00:46,  8.76it/s]\n 19%|█▉        | 95/500 [00:12<00:46,  8.74it/s]\n 19%|█▉        | 96/500 [00:12<00:46,  8.75it/s]\n 19%|█▉        | 97/500 [00:12<00:46,  8.76it/s]\n 20%|█▉        | 98/500 [00:13<00:45,  8.78it/s]\n 20%|█▉        | 99/500 [00:13<00:45,  8.80it/s]\n 20%|██        | 100/500 [00:13<00:45,  8.79it/s]\n 20%|██        | 101/500 [00:13<01:11,  5.56it/s]\n 20%|██        | 102/500 [00:13<01:05,  6.12it/s]\n 21%|██        | 103/500 [00:13<00:59,  6.72it/s]\n 21%|██        | 104/500 [00:14<00:54,  7.23it/s]\n 21%|██        | 105/500 [00:14<00:51,  7.65it/s]\n 21%|██        | 106/500 [00:14<00:49,  7.94it/s]\n 21%|██▏       | 107/500 [00:14<00:48,  8.18it/s]\n 22%|██▏       | 108/500 [00:14<00:46,  8.35it/s]\n 22%|██▏       | 109/500 [00:14<00:46,  8.46it/s]\n 22%|██▏       | 110/500 [00:14<00:45,  8.55it/s]\n 22%|██▏       | 111/500 [00:14<00:45,  8.60it/s]\n 22%|██▏       | 112/500 [00:14<00:44,  8.64it/s]\n 23%|██▎       | 113/500 [00:15<00:44,  8.66it/s]\n 23%|██▎       | 114/500 [00:15<00:44,  8.69it/s]\n 23%|██▎       | 115/500 [00:15<00:44,  8.72it/s]\n 23%|██▎       | 116/500 [00:15<00:43,  8.73it/s]\n 23%|██▎       | 117/500 [00:15<00:43,  8.74it/s]\n 24%|██▎       | 118/500 [00:15<00:43,  8.76it/s]\n 24%|██▍       | 119/500 [00:15<00:43,  8.77it/s]\n 24%|██▍       | 120/500 [00:15<00:44,  8.51it/s]\n 24%|██▍       | 121/500 [00:15<00:44,  8.59it/s]\n 24%|██▍       | 122/500 [00:16<00:43,  8.66it/s]\n 25%|██▍       | 123/500 [00:16<00:43,  8.72it/s]\n 25%|██▍       | 124/500 [00:16<00:42,  8.75it/s]\n 25%|██▌       | 125/500 [00:16<00:42,  8.76it/s]\n 25%|██▌       | 126/500 [00:16<01:06,  5.62it/s]\n 25%|██▌       | 127/500 [00:16<00:59,  6.30it/s]\n 26%|██▌       | 128/500 [00:16<00:54,  6.88it/s]\n 26%|██▌       | 129/500 [00:17<00:50,  7.32it/s]\n 26%|██▌       | 130/500 [00:17<00:48,  7.70it/s]\n 26%|██▌       | 131/500 [00:17<00:46,  7.99it/s]\n 26%|██▋       | 132/500 [00:17<00:44,  8.21it/s]\n 27%|██▋       | 133/500 [00:17<00:43,  8.36it/s]\n 27%|██▋       | 134/500 [00:17<00:43,  8.48it/s]\n 27%|██▋       | 135/500 [00:17<00:42,  8.56it/s]\n 27%|██▋       | 136/500 [00:17<00:42,  8.62it/s]\n 27%|██▋       | 137/500 [00:18<00:41,  8.67it/s]\n 28%|██▊       | 138/500 [00:18<00:41,  8.70it/s]\n 28%|██▊       | 139/500 [00:18<00:41,  8.72it/s]\n 28%|██▊       | 140/500 [00:18<00:41,  8.74it/s]\n 28%|██▊       | 141/500 [00:18<00:41,  8.74it/s]\n 28%|██▊       | 142/500 [00:18<00:40,  8.76it/s]\n 29%|██▊       | 143/500 [00:18<00:40,  8.75it/s]\n 29%|██▉       | 144/500 [00:18<00:40,  8.76it/s]\n 29%|██▉       | 145/500 [00:18<00:40,  8.76it/s]\n 29%|██▉       | 146/500 [00:19<00:40,  8.78it/s]\n 29%|██▉       | 147/500 [00:19<00:40,  8.78it/s]\n 30%|██▉       | 148/500 [00:19<00:40,  8.77it/s]\n 30%|██▉       | 149/500 [00:19<00:40,  8.76it/s]\n 30%|███       | 150/500 [00:19<00:39,  8.77it/s]\n 30%|███       | 151/500 [00:19<01:01,  5.69it/s]\n 30%|███       | 152/500 [00:19<00:54,  6.36it/s]\n 31%|███       | 153/500 [00:20<00:50,  6.92it/s]\n 31%|███       | 154/500 [00:20<00:46,  7.39it/s]\n 31%|███       | 155/500 [00:20<00:44,  7.74it/s]\n 31%|███       | 156/500 [00:20<00:42,  8.02it/s]\n 31%|███▏      | 157/500 [00:20<00:41,  8.23it/s]\n 32%|███▏      | 158/500 [00:20<00:40,  8.41it/s]\n 32%|███▏      | 159/500 [00:20<00:39,  8.53it/s]\n 32%|███▏      | 160/500 [00:20<00:39,  8.60it/s]\n 32%|███▏      | 161/500 [00:20<00:39,  8.64it/s]\n 32%|███▏      | 162/500 [00:21<00:38,  8.69it/s]\n 33%|███▎      | 163/500 [00:21<00:38,  8.72it/s]\n 33%|███▎      | 164/500 [00:21<00:38,  8.73it/s]\n 33%|███▎      | 165/500 [00:21<00:38,  8.74it/s]\n 33%|███▎      | 166/500 [00:21<00:38,  8.75it/s]\n 33%|███▎      | 167/500 [00:21<00:37,  8.77it/s]\n 34%|███▎      | 168/500 [00:21<00:37,  8.79it/s]\n 34%|███▍      | 169/500 [00:21<00:37,  8.78it/s]\n 34%|███▍      | 170/500 [00:21<00:37,  8.78it/s]\n 34%|███▍      | 171/500 [00:22<00:37,  8.78it/s]\n 34%|███▍      | 172/500 [00:22<00:37,  8.77it/s]\n 35%|███▍      | 173/500 [00:22<00:37,  8.76it/s]\n 35%|███▍      | 174/500 [00:22<00:37,  8.76it/s]\n 35%|███▌      | 175/500 [00:22<00:37,  8.76it/s]\n 35%|███▌      | 176/500 [00:22<00:57,  5.64it/s]\n 35%|███▌      | 177/500 [00:22<00:51,  6.22it/s]\n 36%|███▌      | 178/500 [00:23<00:47,  6.81it/s]\n 36%|███▌      | 179/500 [00:23<00:44,  7.28it/s]\n 36%|███▌      | 180/500 [00:23<00:41,  7.68it/s]\n 36%|███▌      | 181/500 [00:23<00:39,  7.99it/s]\n 36%|███▋      | 182/500 [00:23<00:38,  8.21it/s]\n 37%|███▋      | 183/500 [00:23<00:37,  8.38it/s]\n 37%|███▋      | 184/500 [00:23<00:37,  8.49it/s]\n 37%|███▋      | 185/500 [00:23<00:36,  8.56it/s]\n 37%|███▋      | 186/500 [00:24<00:36,  8.63it/s]\n 37%|███▋      | 187/500 [00:24<00:36,  8.65it/s]\n 38%|███▊      | 188/500 [00:24<00:35,  8.68it/s]\n 38%|███▊      | 189/500 [00:24<00:35,  8.71it/s]\n 38%|███▊      | 190/500 [00:24<00:35,  8.75it/s]\n 38%|███▊      | 191/500 [00:24<00:35,  8.77it/s]\n 38%|███▊      | 192/500 [00:24<00:35,  8.79it/s]\n 39%|███▊      | 193/500 [00:24<00:34,  8.78it/s]\n 39%|███▉      | 194/500 [00:24<00:34,  8.77it/s]\n 39%|███▉      | 195/500 [00:25<00:34,  8.76it/s]\n 39%|███▉      | 196/500 [00:25<00:34,  8.77it/s]\n 39%|███▉      | 197/500 [00:25<00:34,  8.77it/s]\n 40%|███▉      | 198/500 [00:25<00:34,  8.76it/s]\n 40%|███▉      | 199/500 [00:25<00:34,  8.78it/s]\n 40%|████      | 200/500 [00:25<00:34,  8.78it/s]\n 40%|████      | 201/500 [00:25<00:55,  5.35it/s]\n 40%|████      | 202/500 [00:26<00:49,  6.05it/s]\n 41%|████      | 203/500 [00:26<00:44,  6.68it/s]\n 41%|████      | 204/500 [00:26<00:41,  7.21it/s]\n 41%|████      | 205/500 [00:26<00:38,  7.63it/s]\n 41%|████      | 206/500 [00:26<00:36,  7.96it/s]\n 41%|████▏     | 207/500 [00:26<00:35,  8.20it/s]\n 42%|████▏     | 208/500 [00:26<00:34,  8.38it/s]\n 42%|████▏     | 209/500 [00:26<00:34,  8.51it/s]\n 42%|████▏     | 210/500 [00:26<00:33,  8.61it/s]\n 42%|████▏     | 211/500 [00:27<00:33,  8.67it/s]\n 42%|████▏     | 212/500 [00:27<00:33,  8.72it/s]\n 43%|████▎     | 213/500 [00:27<00:32,  8.75it/s]\n 43%|████▎     | 214/500 [00:27<00:32,  8.78it/s]\n 43%|████▎     | 215/500 [00:27<00:32,  8.80it/s]\n 43%|████▎     | 216/500 [00:27<00:32,  8.81it/s]\n 43%|████▎     | 217/500 [00:27<00:32,  8.83it/s]\n 44%|████▎     | 218/500 [00:27<00:31,  8.84it/s]\n 44%|████▍     | 219/500 [00:28<00:31,  8.84it/s]\n 44%|████▍     | 220/500 [00:28<00:31,  8.85it/s]\n 44%|████▍     | 221/500 [00:28<00:31,  8.85it/s]\n 44%|████▍     | 222/500 [00:28<00:31,  8.85it/s]\n 45%|████▍     | 223/500 [00:28<00:31,  8.85it/s]\n 45%|████▍     | 224/500 [00:28<00:31,  8.85it/s]\n 45%|████▌     | 225/500 [00:28<00:31,  8.85it/s]\n 45%|████▌     | 226/500 [00:28<00:46,  5.89it/s]\n 45%|████▌     | 227/500 [00:29<00:41,  6.54it/s]\n 46%|████▌     | 228/500 [00:29<00:38,  7.09it/s]\n 46%|████▌     | 229/500 [00:29<00:35,  7.55it/s]\n 46%|████▌     | 230/500 [00:29<00:34,  7.90it/s]\n 46%|████▌     | 231/500 [00:29<00:32,  8.15it/s]\n 46%|████▋     | 232/500 [00:29<00:32,  8.35it/s]\n 47%|████▋     | 233/500 [00:29<00:31,  8.50it/s]\n 47%|████▋     | 234/500 [00:29<00:30,  8.60it/s]\n 47%|████▋     | 235/500 [00:30<00:30,  8.67it/s]\n 47%|████▋     | 236/500 [00:30<00:30,  8.72it/s]\n 47%|████▋     | 237/500 [00:30<00:30,  8.75it/s]\n 48%|████▊     | 238/500 [00:30<00:29,  8.76it/s]\n 48%|████▊     | 239/500 [00:30<00:29,  8.78it/s]\n 48%|████▊     | 240/500 [00:30<00:29,  8.80it/s]\n 48%|████▊     | 241/500 [00:30<00:29,  8.81it/s]\n 48%|████▊     | 242/500 [00:30<00:29,  8.83it/s]\n 49%|████▊     | 243/500 [00:30<00:29,  8.84it/s]\n 49%|████▉     | 244/500 [00:31<00:28,  8.84it/s]\n 49%|████▉     | 245/500 [00:31<00:28,  8.84it/s]\n 49%|████▉     | 246/500 [00:31<00:28,  8.83it/s]\n 49%|████▉     | 247/500 [00:31<00:28,  8.83it/s]\n 50%|████▉     | 248/500 [00:31<00:28,  8.83it/s]\n 50%|████▉     | 249/500 [00:31<00:28,  8.83it/s]\n 50%|█████     | 250/500 [00:31<00:28,  8.84it/s]\n 50%|█████     | 251/500 [00:32<00:41,  5.95it/s]\n 50%|█████     | 252/500 [00:32<00:37,  6.59it/s]\n 51%|█████     | 253/500 [00:32<00:34,  7.13it/s]\n 51%|█████     | 254/500 [00:32<00:32,  7.57it/s]\n 51%|█████     | 255/500 [00:32<00:30,  7.91it/s]\n 51%|█████     | 256/500 [00:32<00:29,  8.17it/s]\n 51%|█████▏    | 257/500 [00:32<00:29,  8.36it/s]\n 52%|█████▏    | 258/500 [00:32<00:28,  8.49it/s]\n 52%|█████▏    | 259/500 [00:32<00:28,  8.59it/s]\n 52%|█████▏    | 260/500 [00:33<00:27,  8.67it/s]\n 52%|█████▏    | 261/500 [00:33<00:27,  8.71it/s]\n 52%|█████▏    | 262/500 [00:33<00:27,  8.74it/s]\n 53%|█████▎    | 263/500 [00:33<00:27,  8.76it/s]\n 53%|█████▎    | 264/500 [00:33<00:26,  8.78it/s]\n 53%|█████▎    | 265/500 [00:33<00:26,  8.79it/s]\n 53%|█████▎    | 266/500 [00:33<00:26,  8.80it/s]\n 53%|█████▎    | 267/500 [00:33<00:26,  8.81it/s]\n 54%|█████▎    | 268/500 [00:33<00:26,  8.81it/s]\n 54%|█████▍    | 269/500 [00:34<00:26,  8.82it/s]\n 54%|█████▍    | 270/500 [00:34<00:26,  8.82it/s]\n 54%|█████▍    | 271/500 [00:34<00:25,  8.83it/s]\n 54%|█████▍    | 272/500 [00:34<00:25,  8.84it/s]\n 55%|█████▍    | 273/500 [00:34<00:25,  8.83it/s]\n 55%|█████▍    | 274/500 [00:34<00:25,  8.83it/s]\n 55%|█████▌    | 275/500 [00:34<00:25,  8.84it/s]\n 55%|█████▌    | 276/500 [00:35<00:42,  5.26it/s]\n 55%|█████▌    | 277/500 [00:35<00:37,  5.97it/s]\n 56%|█████▌    | 278/500 [00:35<00:33,  6.62it/s]\n 56%|█████▌    | 279/500 [00:35<00:30,  7.15it/s]\n 56%|█████▌    | 280/500 [00:35<00:29,  7.58it/s]\n 56%|█████▌    | 281/500 [00:35<00:27,  7.92it/s]\n 56%|█████▋    | 282/500 [00:35<00:26,  8.17it/s]\n 57%|█████▋    | 283/500 [00:35<00:25,  8.36it/s]\n 57%|█████▋    | 284/500 [00:35<00:25,  8.49it/s]\n 57%|█████▋    | 285/500 [00:36<00:25,  8.59it/s]\n 57%|█████▋    | 286/500 [00:36<00:24,  8.66it/s]\n 57%|█████▋    | 287/500 [00:36<00:24,  8.72it/s]\n 58%|█████▊    | 288/500 [00:36<00:24,  8.75it/s]\n 58%|█████▊    | 289/500 [00:36<00:24,  8.77it/s]\n 58%|█████▊    | 290/500 [00:36<00:23,  8.80it/s]\n 58%|█████▊    | 291/500 [00:36<00:23,  8.81it/s]\n 58%|█████▊    | 292/500 [00:36<00:23,  8.81it/s]\n 59%|█████▊    | 293/500 [00:37<00:23,  8.82it/s]\n 59%|█████▉    | 294/500 [00:37<00:23,  8.82it/s]\n 59%|█████▉    | 295/500 [00:37<00:23,  8.81it/s]\n 59%|█████▉    | 296/500 [00:37<00:23,  8.81it/s]\n 59%|█████▉    | 297/500 [00:37<00:23,  8.82it/s]\n 60%|█████▉    | 298/500 [00:37<00:22,  8.81it/s]\n 60%|█████▉    | 299/500 [00:37<00:22,  8.80it/s]\n 60%|██████    | 300/500 [00:37<00:22,  8.81it/s]\n 60%|██████    | 301/500 [00:38<00:39,  5.00it/s]\n 60%|██████    | 302/500 [00:38<00:34,  5.73it/s]\n 61%|██████    | 303/500 [00:38<00:30,  6.41it/s]\n 61%|██████    | 304/500 [00:38<00:28,  6.99it/s]\n 61%|██████    | 305/500 [00:38<00:26,  7.46it/s]\n 61%|██████    | 306/500 [00:38<00:24,  7.83it/s]\n 61%|██████▏   | 307/500 [00:38<00:23,  8.11it/s]\n 62%|██████▏   | 308/500 [00:39<00:23,  8.32it/s]\n 62%|██████▏   | 309/500 [00:39<00:22,  8.47it/s]\n 62%|██████▏   | 310/500 [00:39<00:22,  8.58it/s]\n 62%|██████▏   | 311/500 [00:39<00:21,  8.65it/s]\n 62%|██████▏   | 312/500 [00:39<00:21,  8.71it/s]\n 63%|██████▎   | 313/500 [00:39<00:21,  8.75it/s]\n 63%|██████▎   | 314/500 [00:39<00:21,  8.77it/s]\n 63%|██████▎   | 315/500 [00:39<00:21,  8.79it/s]\n 63%|██████▎   | 316/500 [00:39<00:20,  8.81it/s]\n 63%|██████▎   | 317/500 [00:40<00:20,  8.82it/s]\n 64%|██████▎   | 318/500 [00:40<00:20,  8.83it/s]\n 64%|██████▍   | 319/500 [00:40<00:20,  8.84it/s]\n 64%|██████▍   | 320/500 [00:40<00:20,  8.85it/s]\n 64%|██████▍   | 321/500 [00:40<00:20,  8.85it/s]\n 64%|██████▍   | 322/500 [00:40<00:20,  8.85it/s]\n 65%|██████▍   | 323/500 [00:40<00:19,  8.85it/s]\n 65%|██████▍   | 324/500 [00:40<00:19,  8.85it/s]\n 65%|██████▌   | 325/500 [00:40<00:19,  8.85it/s]\n 65%|██████▌   | 326/500 [00:41<00:36,  4.73it/s]\n 65%|██████▌   | 327/500 [00:41<00:31,  5.49it/s]\n 66%|██████▌   | 328/500 [00:41<00:27,  6.20it/s]\n 66%|██████▌   | 329/500 [00:41<00:25,  6.80it/s]\n 66%|██████▌   | 330/500 [00:41<00:23,  7.31it/s]\n 66%|██████▌   | 331/500 [00:41<00:21,  7.71it/s]\n 66%|██████▋   | 332/500 [00:42<00:20,  8.01it/s]\n 67%|██████▋   | 333/500 [00:42<00:20,  8.24it/s]\n 67%|██████▋   | 334/500 [00:42<00:19,  8.41it/s]\n 67%|██████▋   | 335/500 [00:42<00:19,  8.54it/s]\n 67%|██████▋   | 336/500 [00:42<00:19,  8.63it/s]\n 67%|██████▋   | 337/500 [00:42<00:18,  8.69it/s]\n 68%|██████▊   | 338/500 [00:42<00:18,  8.73it/s]\n 68%|██████▊   | 339/500 [00:42<00:18,  8.77it/s]\n 68%|██████▊   | 340/500 [00:42<00:18,  8.79it/s]\n 68%|██████▊   | 341/500 [00:43<00:18,  8.80it/s]\n 68%|██████▊   | 342/500 [00:43<00:17,  8.81it/s]\n 69%|██████▊   | 343/500 [00:43<00:17,  8.82it/s]\n 69%|██████▉   | 344/500 [00:43<00:17,  8.83it/s]\n 69%|██████▉   | 345/500 [00:43<00:17,  8.84it/s]\n 69%|██████▉   | 346/500 [00:43<00:17,  8.84it/s]\n 69%|██████▉   | 347/500 [00:43<00:17,  8.84it/s]\n 70%|██████▉   | 348/500 [00:43<00:17,  8.84it/s]\n 70%|██████▉   | 349/500 [00:43<00:17,  8.84it/s]\n 70%|███████   | 350/500 [00:44<00:16,  8.84it/s]\n 70%|███████   | 351/500 [00:44<00:30,  4.93it/s]\n 70%|███████   | 352/500 [00:44<00:26,  5.67it/s]\n 71%|███████   | 353/500 [00:44<00:23,  6.36it/s]\n 71%|███████   | 354/500 [00:44<00:21,  6.94it/s]\n 71%|███████   | 355/500 [00:44<00:19,  7.42it/s]\n 71%|███████   | 356/500 [00:45<00:18,  7.80it/s]\n 71%|███████▏  | 357/500 [00:45<00:17,  8.08it/s]\n 72%|███████▏  | 358/500 [00:45<00:17,  8.29it/s]\n 72%|███████▏  | 359/500 [00:45<00:16,  8.45it/s]\n 72%|███████▏  | 360/500 [00:45<00:16,  8.56it/s]\n 72%|███████▏  | 361/500 [00:45<00:16,  8.65it/s]\n 72%|███████▏  | 362/500 [00:45<00:15,  8.70it/s]\n 73%|███████▎  | 363/500 [00:45<00:15,  8.73it/s]\n 73%|███████▎  | 364/500 [00:45<00:15,  8.76it/s]\n 73%|███████▎  | 365/500 [00:46<00:15,  8.79it/s]\n 73%|███████▎  | 366/500 [00:46<00:15,  8.80it/s]\n 73%|███████▎  | 367/500 [00:46<00:15,  8.81it/s]\n 74%|███████▎  | 368/500 [00:46<00:14,  8.82it/s]\n 74%|███████▍  | 369/500 [00:46<00:14,  8.83it/s]\n 74%|███████▍  | 370/500 [00:46<00:14,  8.83it/s]\n 74%|███████▍  | 371/500 [00:46<00:14,  8.83it/s]\n 74%|███████▍  | 372/500 [00:46<00:14,  8.83it/s]\n 75%|███████▍  | 373/500 [00:46<00:14,  8.82it/s]\n 75%|███████▍  | 374/500 [00:47<00:14,  8.83it/s]\n 75%|███████▌  | 375/500 [00:47<00:14,  8.83it/s]\n 75%|███████▌  | 376/500 [00:47<00:25,  4.90it/s]\n 75%|███████▌  | 377/500 [00:47<00:21,  5.65it/s]\n 76%|███████▌  | 378/500 [00:47<00:19,  6.33it/s]\n 76%|███████▌  | 379/500 [00:47<00:17,  6.92it/s]\n 76%|███████▌  | 380/500 [00:48<00:16,  7.41it/s]\n 76%|███████▌  | 381/500 [00:48<00:15,  7.79it/s]\n 76%|███████▋  | 382/500 [00:48<00:14,  8.08it/s]\n 77%|███████▋  | 383/500 [00:48<00:14,  8.29it/s]\n 77%|███████▋  | 384/500 [00:48<00:13,  8.41it/s]\n 77%|███████▋  | 385/500 [00:48<00:13,  8.54it/s]\n 77%|███████▋  | 386/500 [00:48<00:13,  8.63it/s]\n 77%|███████▋  | 387/500 [00:48<00:12,  8.69it/s]\n 78%|███████▊  | 388/500 [00:48<00:12,  8.74it/s]\n 78%|███████▊  | 389/500 [00:49<00:12,  8.77it/s]\n 78%|███████▊  | 390/500 [00:49<00:12,  8.80it/s]\n 78%|███████▊  | 391/500 [00:49<00:12,  8.82it/s]\n 78%|███████▊  | 392/500 [00:49<00:12,  8.84it/s]\n 79%|███████▊  | 393/500 [00:49<00:12,  8.84it/s]\n 79%|███████▉  | 394/500 [00:49<00:11,  8.85it/s]\n 79%|███████▉  | 395/500 [00:49<00:11,  8.86it/s]\n 79%|███████▉  | 396/500 [00:49<00:11,  8.86it/s]\n 79%|███████▉  | 397/500 [00:50<00:11,  8.86it/s]\n 80%|███████▉  | 398/500 [00:50<00:11,  8.86it/s]\n 80%|███████▉  | 399/500 [00:50<00:11,  8.85it/s]\n 80%|████████  | 400/500 [00:50<00:11,  8.85it/s]\n 80%|████████  | 401/500 [00:50<00:16,  6.16it/s]\n 80%|████████  | 402/500 [00:50<00:14,  6.77it/s]\n 81%|████████  | 403/500 [00:50<00:13,  7.29it/s]\n 81%|████████  | 404/500 [00:50<00:12,  7.70it/s]\n 81%|████████  | 405/500 [00:51<00:11,  8.02it/s]\n 81%|████████  | 406/500 [00:51<00:11,  8.25it/s]\n 81%|████████▏ | 407/500 [00:51<00:11,  8.42it/s]\n 82%|████████▏ | 408/500 [00:51<00:10,  8.55it/s]\n 82%|████████▏ | 409/500 [00:51<00:10,  8.63it/s]\n 82%|████████▏ | 410/500 [00:51<00:10,  8.69it/s]\n 82%|████████▏ | 411/500 [00:51<00:10,  8.74it/s]\n 82%|████████▏ | 412/500 [00:51<00:10,  8.78it/s]\n 83%|████████▎ | 413/500 [00:51<00:09,  8.80it/s]\n 83%|████████▎ | 414/500 [00:52<00:09,  8.82it/s]\n 83%|████████▎ | 415/500 [00:52<00:09,  8.83it/s]\n 83%|████████▎ | 416/500 [00:52<00:09,  8.84it/s]\n 83%|████████▎ | 417/500 [00:52<00:09,  8.85it/s]\n 84%|████████▎ | 418/500 [00:52<00:09,  8.85it/s]\n 84%|████████▍ | 419/500 [00:52<00:09,  8.86it/s]\n 84%|████████▍ | 420/500 [00:52<00:09,  8.86it/s]\n 84%|████████▍ | 421/500 [00:52<00:08,  8.86it/s]\n 84%|████████▍ | 422/500 [00:52<00:08,  8.84it/s]\n 85%|████████▍ | 423/500 [00:53<00:08,  8.84it/s]\n 85%|████████▍ | 424/500 [00:53<00:08,  8.84it/s]\n 85%|████████▌ | 425/500 [00:53<00:08,  8.84it/s]\n 85%|████████▌ | 426/500 [00:53<00:13,  5.46it/s]\n 85%|████████▌ | 427/500 [00:53<00:11,  6.16it/s]\n 86%|████████▌ | 428/500 [00:53<00:10,  6.77it/s]\n 86%|████████▌ | 429/500 [00:54<00:09,  7.29it/s]\n 86%|████████▌ | 430/500 [00:54<00:09,  7.69it/s]\n 86%|████████▌ | 431/500 [00:54<00:08,  8.01it/s]\n 86%|████████▋ | 432/500 [00:54<00:08,  8.24it/s]\n 87%|████████▋ | 433/500 [00:54<00:07,  8.41it/s]\n 87%|████████▋ | 434/500 [00:54<00:07,  8.53it/s]\n 87%|████████▋ | 435/500 [00:54<00:07,  8.62it/s]\n 87%|████████▋ | 436/500 [00:54<00:07,  8.68it/s]\n 87%|████████▋ | 437/500 [00:54<00:07,  8.73it/s]\n 88%|████████▊ | 438/500 [00:55<00:07,  8.77it/s]\n 88%|████████▊ | 439/500 [00:55<00:06,  8.79it/s]\n 88%|████████▊ | 440/500 [00:55<00:06,  8.80it/s]\n 88%|████████▊ | 441/500 [00:55<00:06,  8.80it/s]\n 88%|████████▊ | 442/500 [00:55<00:06,  8.80it/s]\n 89%|████████▊ | 443/500 [00:55<00:06,  8.81it/s]\n 89%|████████▉ | 444/500 [00:55<00:06,  8.81it/s]\n 89%|████████▉ | 445/500 [00:55<00:06,  8.80it/s]\n 89%|████████▉ | 446/500 [00:55<00:06,  8.82it/s]\n 89%|████████▉ | 447/500 [00:56<00:06,  8.83it/s]\n 90%|████████▉ | 448/500 [00:56<00:05,  8.84it/s]\n 90%|████████▉ | 449/500 [00:56<00:05,  8.85it/s]\n 90%|█████████ | 450/500 [00:56<00:05,  8.86it/s]\n 90%|█████████ | 451/500 [00:56<00:07,  6.21it/s]\n 90%|█████████ | 452/500 [00:56<00:07,  6.81it/s]\n 91%|█████████ | 453/500 [00:56<00:06,  7.32it/s]\n 91%|█████████ | 454/500 [00:57<00:05,  7.73it/s]\n 91%|█████████ | 455/500 [00:57<00:05,  8.03it/s]\n 91%|█████████ | 456/500 [00:57<00:05,  8.26it/s]\n 91%|█████████▏| 457/500 [00:57<00:05,  8.43it/s]\n 92%|█████████▏| 458/500 [00:57<00:04,  8.55it/s]\n 92%|█████████▏| 459/500 [00:57<00:04,  8.64it/s]\n 92%|█████████▏| 460/500 [00:57<00:04,  8.71it/s]\n 92%|█████████▏| 461/500 [00:57<00:04,  8.75it/s]\n 92%|█████████▏| 462/500 [00:57<00:04,  8.78it/s]\n 93%|█████████▎| 463/500 [00:58<00:04,  8.81it/s]\n 93%|█████████▎| 464/500 [00:58<00:04,  8.82it/s]\n 93%|█████████▎| 465/500 [00:58<00:03,  8.82it/s]\n 93%|█████████▎| 466/500 [00:58<00:03,  8.82it/s]\n 93%|█████████▎| 467/500 [00:58<00:03,  8.81it/s]\n 94%|█████████▎| 468/500 [00:58<00:03,  8.83it/s]\n 94%|█████████▍| 469/500 [00:58<00:03,  8.83it/s]\n 94%|█████████▍| 470/500 [00:58<00:03,  8.83it/s]\n 94%|█████████▍| 471/500 [00:58<00:03,  8.83it/s]\n 94%|█████████▍| 472/500 [00:59<00:03,  8.83it/s]\n 95%|█████████▍| 473/500 [00:59<00:03,  8.84it/s]\n 95%|█████████▍| 474/500 [00:59<00:02,  8.85it/s]\n 95%|█████████▌| 475/500 [00:59<00:02,  8.85it/s]\n 95%|█████████▌| 476/500 [00:59<00:03,  6.22it/s]\n 95%|█████████▌| 477/500 [00:59<00:03,  6.82it/s]\n 96%|█████████▌| 478/500 [00:59<00:03,  7.32it/s]\n 96%|█████████▌| 479/500 [00:59<00:02,  7.72it/s]\n 96%|█████████▌| 480/500 [01:00<00:02,  8.02it/s]\n 96%|█████████▌| 481/500 [01:00<00:02,  8.25it/s]\n 96%|█████████▋| 482/500 [01:00<00:02,  8.43it/s]\n 97%|█████████▋| 483/500 [01:00<00:01,  8.55it/s]\n 97%|█████████▋| 484/500 [01:00<00:01,  8.64it/s]\n 97%|█████████▋| 485/500 [01:00<00:01,  8.71it/s]\n 97%|█████████▋| 486/500 [01:00<00:01,  8.75it/s]\n 97%|█████████▋| 487/500 [01:00<00:01,  8.78it/s]\n 98%|█████████▊| 488/500 [01:01<00:01,  8.81it/s]\n 98%|█████████▊| 489/500 [01:01<00:01,  8.83it/s]\n 98%|█████████▊| 490/500 [01:01<00:01,  8.84it/s]\n 98%|█████████▊| 491/500 [01:01<00:01,  8.85it/s]\n 98%|█████████▊| 492/500 [01:01<00:00,  8.84it/s]\n 99%|█████████▊| 493/500 [01:01<00:00,  8.84it/s]\n 99%|█████████▉| 494/500 [01:01<00:00,  8.84it/s]\n 99%|█████████▉| 495/500 [01:01<00:00,  8.83it/s]\n 99%|█████████▉| 496/500 [01:01<00:00,  8.83it/s]\n 99%|█████████▉| 497/500 [01:02<00:00,  8.84it/s]\n100%|█████████▉| 498/500 [01:02<00:00,  8.84it/s]\n100%|█████████▉| 499/500 [01:02<00:00,  8.84it/s]\n100%|██████████| 500/500 [01:02<00:00,  8.84it/s]\n100%|██████████| 500/500 [01:02<00:00,  8.02it/s]",
  "metrics": {
    "predict_time": 87.166102,
    "total_time": 87.442241
  },
  "output": [
    "https://replicate.delivery/mgxm/9143aab6-0adf-4c5b-a58c-e38166a48c58/00000.png"
  ],
  "started_at": "2022-10-10T19:34:29.243111Z",
  "status": "succeeded",
  "urls": {
    "get": "https://api.replicate.com/v1/predictions/thh6qyqtmjbd5adxy7w5s3pfhy",
    "cancel": "https://api.replicate.com/v1/predictions/thh6qyqtmjbd5adxy7w5s3pfhy/cancel"
  },
  "version": "760f4043f4f53f4bb5e9b3d1f9268030ae514638e77732916344f1dd4b305607"
}

Generated in

87.2 seconds

Tweak itReport

$ /root/.pyenv/versions/3.10.7/bin/python sample.py --model_path inpaint.pt --edit /tmp/tmpc_o91y0t205032562_345087143808969_4674423480430035886_n.png --mask /tmp/tmpvkqeu1cpface_mask.png --steps 500 --text Jon snow from the game of thrones --num_batches 1
Using device: cuda:0
making attention of type 'vanilla' with 512 in_channels
Working with z of shape (1, 4, 32, 32) = 4096 dimensions.
making attention of type 'vanilla' with 512 in_channels
Some weights of the model checkpoint at openai/clip-vit-large-patch14 were not used when initializing CLIPTextModel: ['vision_model.encoder.layers.19.self_attn.k_proj.bias', 'vision_model.encoder.layers.21.layer_norm1.weight', 'vision_model.encoder.layers.0.self_attn.out_proj.bias', 'vision_model.encoder.layers.14.layer_norm1.bias', 'vision_model.encoder.layers.21.mlp.fc2.weight', 'vision_model.encoder.layers.3.mlp.fc1.bias', 'vision_model.encoder.layers.11.mlp.fc1.weight', 'vision_model.encoder.layers.3.self_attn.v_proj.bias', 'vision_model.encoder.layers.10.mlp.fc2.weight', 'vision_model.encoder.layers.8.self_attn.q_proj.bias', 'vision_model.encoder.layers.6.layer_norm1.bias', 'vision_model.encoder.layers.18.self_attn.k_proj.bias', 'vision_model.encoder.layers.8.layer_norm2.bias', 'vision_model.encoder.layers.20.mlp.fc1.bias', 'vision_model.encoder.layers.2.layer_norm1.bias', 'vision_model.encoder.layers.17.self_attn.v_proj.bias', 'vision_model.encoder.layers.1.self_attn.q_proj.bias', 'vision_model.encoder.layers.8.mlp.fc1.weight', 'vision_model.encoder.layers.13.layer_norm1.bias', 'vision_model.encoder.layers.21.self_attn.q_proj.weight', 'vision_model.encoder.layers.13.self_attn.k_proj.bias', 'vision_model.encoder.layers.10.self_attn.v_proj.bias', 'vision_model.encoder.layers.6.layer_norm2.weight', 'vision_model.encoder.layers.11.layer_norm2.weight', 'vision_model.encoder.layers.18.mlp.fc2.weight', 'vision_model.encoder.layers.8.layer_norm1.bias', 'vision_model.encoder.layers.4.mlp.fc2.weight', 'vision_model.encoder.layers.2.self_attn.out_proj.weight', 'vision_model.encoder.layers.8.mlp.fc1.bias', 'vision_model.encoder.layers.11.mlp.fc2.bias', 'vision_model.encoder.layers.17.layer_norm1.bias', 'vision_model.encoder.layers.2.layer_norm2.weight', 'vision_model.embeddings.position_ids', 'vision_model.encoder.layers.2.mlp.fc1.weight', 'vision_model.encoder.layers.20.self_attn.v_proj.bias', 'vision_model.encoder.layers.17.layer_norm2.bias', 'vision_model.encoder.layers.4.self_attn.out_proj.weight', 'vision_model.encoder.layers.4.self_attn.v_proj.weight', 'vision_model.encoder.layers.17.self_attn.q_proj.weight', 'vision_model.encoder.layers.20.self_attn.v_proj.weight', 'vision_model.encoder.layers.7.mlp.fc2.weight', 'vision_model.encoder.layers.3.layer_norm1.weight', 'vision_model.encoder.layers.22.self_attn.v_proj.weight', 'vision_model.encoder.layers.21.layer_norm1.bias', 'vision_model.encoder.layers.2.mlp.fc2.bias', 'vision_model.encoder.layers.4.self_attn.q_proj.bias', 'vision_model.encoder.layers.6.self_attn.k_proj.weight', 'vision_model.encoder.layers.6.layer_norm2.bias', 'vision_model.encoder.layers.11.mlp.fc2.weight', 'vision_model.encoder.layers.15.mlp.fc1.bias', 'vision_model.encoder.layers.15.layer_norm2.weight', 'vision_model.encoder.layers.4.self_attn.k_proj.weight', 'vision_model.encoder.layers.9.self_attn.v_proj.weight', 'vision_model.encoder.layers.16.self_attn.q_proj.weight', 'vision_model.encoder.layers.10.layer_norm1.bias', 'vision_model.encoder.layers.9.self_attn.k_proj.bias', 'vision_model.encoder.layers.7.self_attn.q_proj.weight', 'vision_model.encoder.layers.13.self_attn.q_proj.bias', 'vision_model.encoder.layers.5.layer_norm2.bias', 'vision_model.encoder.layers.15.self_attn.q_proj.weight', 'vision_model.encoder.layers.15.mlp.fc1.weight', 'vision_model.encoder.layers.21.self_attn.out_proj.weight', 'vision_model.encoder.layers.13.self_attn.q_proj.weight', 'vision_model.encoder.layers.19.self_attn.q_proj.weight', 'vision_model.encoder.layers.17.self_attn.out_proj.weight', 'vision_model.encoder.layers.10.self_attn.out_proj.bias', 'vision_model.encoder.layers.19.mlp.fc2.weight', 'vision_model.encoder.layers.13.self_attn.out_proj.bias', 'vision_model.encoder.layers.16.mlp.fc2.weight', 'vision_model.encoder.layers.3.mlp.fc1.weight', 'vision_model.encoder.layers.4.mlp.fc1.bias', 'vision_model.encoder.layers.0.mlp.fc2.bias', 'vision_model.encoder.layers.21.mlp.fc2.bias', 'vision_model.encoder.layers.18.layer_norm2.bias', 'vision_model.encoder.layers.23.mlp.fc2.bias', 'vision_model.encoder.layers.8.mlp.fc2.bias', 'vision_model.encoder.layers.21.self_attn.k_proj.weight', 'vision_model.encoder.layers.7.mlp.fc1.bias', 'vision_model.encoder.layers.19.layer_norm1.weight', 'vision_model.encoder.layers.0.layer_norm1.weight', 'vision_model.encoder.layers.4.mlp.fc1.weight', 'vision_model.encoder.layers.16.self_attn.q_proj.bias', 'vision_model.encoder.layers.1.layer_norm2.bias', 'vision_model.encoder.layers.20.layer_norm2.bias', 'vision_model.encoder.layers.12.self_attn.k_proj.bias', 'vision_model.encoder.layers.4.layer_norm1.weight', 'vision_model.encoder.layers.20.self_attn.q_proj.bias', 'vision_model.encoder.layers.6.self_attn.q_proj.bias', 'vision_model.encoder.layers.3.layer_norm2.weight', 'vision_model.encoder.layers.4.self_attn.k_proj.bias', 'vision_model.encoder.layers.5.self_attn.out_proj.bias', 'vision_model.encoder.layers.10.mlp.fc1.weight', 'vision_model.encoder.layers.17.self_attn.out_proj.bias', 'vision_model.encoder.layers.5.layer_norm1.weight', 'vision_model.encoder.layers.7.mlp.fc1.weight', 'vision_model.encoder.layers.2.self_attn.q_proj.weight', 'vision_model.encoder.layers.7.layer_norm2.bias', 'vision_model.encoder.layers.0.mlp.fc1.bias', 'vision_model.encoder.layers.8.self_attn.v_proj.weight', 'text_projection.weight', 'vision_model.encoder.layers.6.mlp.fc1.weight', 'vision_model.encoder.layers.20.layer_norm1.weight', 'vision_model.encoder.layers.21.self_attn.v_proj.weight', 'vision_model.encoder.layers.8.self_attn.k_proj.weight', 'vision_model.encoder.layers.13.self_attn.v_proj.bias', 'vision_model.encoder.layers.8.self_attn.out_proj.weight', 'vision_model.encoder.layers.13.self_attn.k_proj.weight', 'vision_model.encoder.layers.8.self_attn.out_proj.bias', 'vision_model.encoder.layers.12.layer_norm1.bias', 'vision_model.encoder.layers.7.self_attn.out_proj.bias', 'vision_model.encoder.layers.20.layer_norm1.bias', 'vision_model.encoder.layers.15.self_attn.k_proj.weight', 'vision_model.encoder.layers.22.mlp.fc1.weight', 'vision_model.encoder.layers.11.self_attn.q_proj.weight', 'vision_model.encoder.layers.1.self_attn.k_proj.bias', 'vision_model.encoder.layers.14.self_attn.k_proj.weight', 'vision_model.encoder.layers.22.self_attn.k_proj.bias', 'vision_model.encoder.layers.3.self_attn.q_proj.bias', 'vision_model.encoder.layers.12.mlp.fc1.bias', 'vision_model.encoder.layers.8.layer_norm2.weight', 'vision_model.encoder.layers.19.self_attn.k_proj.weight', 'vision_model.encoder.layers.17.layer_norm1.weight', 'vision_model.encoder.layers.17.self_attn.k_proj.weight', 'vision_model.encoder.layers.13.layer_norm1.weight', 'vision_model.encoder.layers.22.self_attn.out_proj.bias', 'vision_model.encoder.layers.8.self_attn.k_proj.bias', 'vision_model.encoder.layers.10.self_attn.k_proj.bias', 'vision_model.encoder.layers.18.self_attn.v_proj.weight', 'vision_model.encoder.layers.18.self_attn.out_proj.bias', 'vision_model.encoder.layers.15.layer_norm1.weight', 'vision_model.encoder.layers.13.mlp.fc2.bias', 'vision_model.encoder.layers.23.layer_norm1.bias', 'vision_model.encoder.layers.7.self_attn.q_proj.bias', 'vision_model.encoder.layers.18.layer_norm1.bias', 'vision_model.encoder.layers.23.mlp.fc1.weight', 'vision_model.encoder.layers.16.self_attn.v_proj.weight', 'vision_model.encoder.layers.20.self_attn.k_proj.weight', 'vision_model.encoder.layers.11.self_attn.v_proj.bias', 'vision_model.encoder.layers.19.mlp.fc2.bias', 'vision_model.encoder.layers.13.mlp.fc1.bias', 'vision_model.encoder.layers.3.self_attn.out_proj.bias', 'vision_model.encoder.layers.3.mlp.fc2.bias', 'vision_model.encoder.layers.2.self_attn.v_proj.weight', 'vision_model.encoder.layers.5.mlp.fc1.bias', 'vision_model.encoder.layers.5.mlp.fc2.bias', 'vision_model.encoder.layers.1.mlp.fc2.bias', 'vision_model.encoder.layers.19.layer_norm2.bias', 'vision_model.encoder.layers.15.layer_norm1.bias', 'vision_model.encoder.layers.16.self_attn.k_proj.bias', 'vision_model.encoder.layers.3.self_attn.k_proj.weight', 'vision_model.encoder.layers.3.layer_norm2.bias', 'vision_model.encoder.layers.18.mlp.fc1.bias', 'vision_model.encoder.layers.7.layer_norm2.weight', 'vision_model.encoder.layers.2.self_attn.v_proj.bias', 'vision_model.encoder.layers.3.self_attn.k_proj.bias', 'vision_model.encoder.layers.0.self_attn.v_proj.weight', 'vision_model.encoder.layers.0.self_attn.q_proj.bias', 'vision_model.encoder.layers.12.self_attn.v_proj.bias', 'vision_model.encoder.layers.14.layer_norm1.weight', 'vision_model.encoder.layers.4.layer_norm2.bias', 'vision_model.encoder.layers.20.self_attn.out_proj.bias', 'vision_model.encoder.layers.12.self_attn.out_proj.bias', 'vision_model.encoder.layers.6.mlp.fc2.weight', 'vision_model.encoder.layers.21.self_attn.out_proj.bias', 'vision_model.encoder.layers.22.mlp.fc2.bias', 'vision_model.encoder.layers.18.mlp.fc2.bias', 'vision_model.embeddings.patch_embedding.weight', 'vision_model.encoder.layers.9.self_attn.v_proj.bias', 'vision_model.encoder.layers.13.self_attn.v_proj.weight', 'vision_model.encoder.layers.9.layer_norm2.weight', 'vision_model.encoder.layers.10.layer_norm2.bias', 'vision_model.encoder.layers.22.layer_norm2.bias', 'vision_model.encoder.layers.22.layer_norm2.weight', 'vision_model.encoder.layers.0.self_attn.k_proj.bias', 'vision_model.encoder.layers.0.self_attn.k_proj.weight', 'vision_model.encoder.layers.7.self_attn.v_proj.weight', 'vision_model.encoder.layers.3.self_attn.q_proj.weight', 'vision_model.encoder.layers.16.self_attn.v_proj.bias', 'vision_model.encoder.layers.23.self_attn.out_proj.weight', 'vision_model.encoder.layers.10.self_attn.out_proj.weight', 'vision_model.encoder.layers.14.self_attn.v_proj.bias', 'vision_model.encoder.layers.4.mlp.fc2.bias', 'vision_model.encoder.layers.11.self_attn.v_proj.weight', 'vision_model.encoder.layers.12.mlp.fc2.weight', 'vision_model.encoder.layers.7.self_attn.v_proj.bias', 'vision_model.encoder.layers.1.self_attn.q_proj.weight', 'vision_model.encoder.layers.19.layer_norm2.weight', 'vision_model.encoder.layers.21.layer_norm2.bias', 'vision_model.encoder.layers.2.self_attn.k_proj.weight', 'vision_model.encoder.layers.18.self_attn.k_proj.weight', 'vision_model.encoder.layers.13.self_attn.out_proj.weight', 'vision_model.encoder.layers.21.self_attn.q_proj.bias', 'vision_model.encoder.layers.20.self_attn.out_proj.weight', 'vision_model.encoder.layers.16.self_attn.k_proj.weight', 'vision_model.encoder.layers.6.self_attn.v_proj.weight', 'vision_model.encoder.layers.11.self_attn.out_proj.weight', 'vision_model.encoder.layers.2.layer_norm1.weight', 'vision_model.encoder.layers.7.layer_norm1.bias', 'vision_model.encoder.layers.14.self_attn.v_proj.weight', 'vision_model.encoder.layers.16.layer_norm1.bias', 'vision_model.encoder.layers.15.layer_norm2.bias', 'vision_model.encoder.layers.16.mlp.fc1.bias', 'vision_model.encoder.layers.20.mlp.fc2.bias', 'vision_model.encoder.layers.23.self_attn.v_proj.bias', 'vision_model.encoder.layers.3.mlp.fc2.weight', 'vision_model.encoder.layers.23.layer_norm2.weight', 'vision_model.encoder.layers.20.self_attn.k_proj.bias', 'vision_model.encoder.layers.6.layer_norm1.weight', 'vision_model.encoder.layers.1.self_attn.out_proj.bias', 'vision_model.encoder.layers.6.mlp.fc2.bias', 'vision_model.encoder.layers.22.self_attn.q_proj.bias', 'vision_model.encoder.layers.9.mlp.fc2.bias', 'vision_model.encoder.layers.7.mlp.fc2.bias', 'vision_model.encoder.layers.23.layer_norm1.weight', 'vision_model.encoder.layers.6.self_attn.v_proj.bias', 'vision_model.encoder.layers.4.self_attn.out_proj.bias', 'vision_model.encoder.layers.21.layer_norm2.weight', 'vision_model.encoder.layers.2.mlp.fc2.weight', 'vision_model.encoder.layers.0.self_attn.out_proj.weight', 'vision_model.encoder.layers.6.self_attn.k_proj.bias', 'vision_model.encoder.layers.22.mlp.fc2.weight', 'vision_model.embeddings.position_embedding.weight', 'vision_model.encoder.layers.15.mlp.fc2.weight', 'vision_model.encoder.layers.3.layer_norm1.bias', 'vision_model.encoder.layers.5.self_attn.v_proj.weight', 'vision_model.encoder.layers.10.mlp.fc1.bias', 'vision_model.encoder.layers.2.layer_norm2.bias', 'vision_model.encoder.layers.16.self_attn.out_proj.bias', 'vision_model.encoder.layers.21.mlp.fc1.bias', 'vision_model.encoder.layers.6.self_attn.out_proj.weight', 'vision_model.encoder.layers.6.self_attn.q_proj.weight', 'vision_model.encoder.layers.5.layer_norm1.bias', 'vision_model.encoder.layers.10.layer_norm1.weight', 'vision_model.encoder.layers.13.layer_norm2.bias', 'vision_model.encoder.layers.23.self_attn.q_proj.weight', 'vision_model.encoder.layers.7.self_attn.out_proj.weight', 'vision_model.encoder.layers.11.self_attn.q_proj.bias', 'vision_model.encoder.layers.5.layer_norm2.weight', 'vision_model.encoder.layers.16.layer_norm2.bias', 'vision_model.encoder.layers.16.layer_norm2.weight', 'vision_model.encoder.layers.10.self_attn.q_proj.bias', 'vision_model.encoder.layers.0.layer_norm2.weight', 'vision_model.encoder.layers.12.self_attn.q_proj.bias', 'vision_model.encoder.layers.11.self_attn.k_proj.bias', 'vision_model.encoder.layers.7.layer_norm1.weight', 'vision_model.encoder.layers.7.self_attn.k_proj.bias', 'vision_model.encoder.layers.11.layer_norm2.bias', 'vision_model.encoder.layers.21.self_attn.k_proj.bias', 'vision_model.encoder.layers.21.self_attn.v_proj.bias', 'vision_model.encoder.layers.9.self_attn.q_proj.bias', 'vision_model.encoder.layers.15.self_attn.v_proj.weight', 'vision_model.encoder.layers.10.self_attn.q_proj.weight', 'vision_model.encoder.layers.6.self_attn.out_proj.bias', 'vision_model.encoder.layers.20.layer_norm2.weight', 'vision_model.encoder.layers.2.self_attn.k_proj.bias', 'vision_model.pre_layrnorm.weight', 'vision_model.encoder.layers.18.self_attn.out_proj.weight', 'vision_model.encoder.layers.19.mlp.fc1.weight', 'vision_model.encoder.layers.13.mlp.fc2.weight', 'vision_model.encoder.layers.22.self_attn.k_proj.weight', 'vision_model.encoder.layers.17.mlp.fc2.bias', 'vision_model.encoder.layers.23.mlp.fc1.bias', 'vision_model.encoder.layers.7.self_attn.k_proj.weight', 'vision_model.encoder.layers.11.mlp.fc1.bias', 'vision_model.encoder.layers.10.layer_norm2.weight', 'vision_model.encoder.layers.21.mlp.fc1.weight', 'vision_model.encoder.layers.14.self_attn.q_proj.bias', 'vision_model.encoder.layers.5.self_attn.q_proj.bias', 'vision_model.encoder.layers.1.self_attn.out_proj.weight', 'vision_model.encoder.layers.14.mlp.fc1.bias', 'vision_model.encoder.layers.17.self_attn.q_proj.bias', 'vision_model.encoder.layers.14.self_attn.q_proj.weight', 'vision_model.encoder.layers.12.layer_norm1.weight', 'vision_model.encoder.layers.18.self_attn.q_proj.weight', 'vision_model.encoder.layers.15.self_attn.v_proj.bias', 'vision_model.encoder.layers.2.mlp.fc1.bias', 'vision_model.pre_layrnorm.bias', 'vision_model.encoder.layers.23.self_attn.k_proj.weight', 'vision_model.encoder.layers.14.self_attn.out_proj.weight', 'vision_model.encoder.layers.8.self_attn.q_proj.weight', 'vision_model.encoder.layers.10.mlp.fc2.bias', 'vision_model.encoder.layers.17.mlp.fc2.weight', 'vision_model.encoder.layers.8.layer_norm1.weight', 'vision_model.encoder.layers.11.self_attn.k_proj.weight', 'vision_model.encoder.layers.15.self_attn.out_proj.weight', 'vision_model.encoder.layers.8.mlp.fc2.weight', 'vision_model.encoder.layers.19.layer_norm1.bias', 'vision_model.encoder.layers.8.self_attn.v_proj.bias', 'vision_model.encoder.layers.22.self_attn.q_proj.weight', 'vision_model.encoder.layers.23.self_attn.k_proj.bias', 'vision_model.encoder.layers.0.mlp.fc1.weight', 'vision_model.encoder.layers.16.layer_norm1.weight', 'vision_model.encoder.layers.18.layer_norm1.weight', 'vision_model.encoder.layers.2.self_attn.out_proj.bias', 'vision_model.encoder.layers.9.self_attn.q_proj.weight', 'vision_model.encoder.layers.15.self_attn.q_proj.bias', 'vision_model.encoder.layers.17.self_attn.v_proj.weight', 'vision_model.encoder.layers.14.layer_norm2.bias', 'vision_model.encoder.layers.14.self_attn.out_proj.bias', 'vision_model.encoder.layers.1.self_attn.k_proj.weight', 'vision_model.encoder.layers.11.self_attn.out_proj.bias', 'vision_model.encoder.layers.12.self_attn.out_proj.weight', 'vision_model.encoder.layers.20.mlp.fc2.weight', 'vision_model.encoder.layers.9.mlp.fc2.weight', 'vision_model.encoder.layers.23.mlp.fc2.weight', 'vision_model.encoder.layers.5.self_attn.q_proj.weight', 'vision_model.encoder.layers.0.self_attn.v_proj.bias', 'vision_model.encoder.layers.4.layer_norm1.bias', 'vision_model.encoder.layers.17.mlp.fc1.bias', 'vision_model.encoder.layers.20.mlp.fc1.weight', 'vision_model.encoder.layers.5.mlp.fc2.weight', 'vision_model.encoder.layers.23.self_attn.q_proj.bias', 'vision_model.encoder.layers.11.layer_norm1.weight', 'vision_model.encoder.layers.1.mlp.fc1.bias', 'vision_model.encoder.layers.10.self_attn.k_proj.weight', 'vision_model.encoder.layers.1.self_attn.v_proj.weight', 'vision_model.encoder.layers.0.self_attn.q_proj.weight', 'vision_model.encoder.layers.23.self_attn.out_proj.bias', 'vision_model.encoder.layers.22.layer_norm1.bias', 'vision_model.encoder.layers.14.layer_norm2.weight', 'vision_model.encoder.layers.15.self_attn.k_proj.bias', 'vision_model.encoder.layers.13.layer_norm2.weight', 'vision_model.encoder.layers.9.layer_norm1.bias', 'vision_model.encoder.layers.20.self_attn.q_proj.weight', 'vision_model.encoder.layers.6.mlp.fc1.bias', 'vision_model.encoder.layers.9.self_attn.k_proj.weight', 'vision_model.encoder.layers.17.layer_norm2.weight', 'vision_model.encoder.layers.18.self_attn.v_proj.bias', 'vision_model.encoder.layers.4.self_attn.v_proj.bias', 'vision_model.encoder.layers.3.self_attn.v_proj.weight', 'vision_model.encoder.layers.9.self_attn.out_proj.bias', 'vision_model.encoder.layers.19.self_attn.v_proj.weight', 'vision_model.encoder.layers.9.mlp.fc1.bias', 'vision_model.encoder.layers.1.layer_norm2.weight', 'vision_model.encoder.layers.16.self_attn.out_proj.weight', 'vision_model.encoder.layers.19.self_attn.q_proj.bias', 'vision_model.encoder.layers.0.layer_norm2.bias', 'vision_model.encoder.layers.5.self_attn.out_proj.weight', 'vision_model.encoder.layers.15.self_attn.out_proj.bias', 'vision_model.encoder.layers.12.layer_norm2.bias', 'vision_model.encoder.layers.9.layer_norm2.bias', 'vision_model.encoder.layers.1.layer_norm1.bias', 'vision_model.encoder.layers.22.mlp.fc1.bias', 'vision_model.encoder.layers.14.mlp.fc1.weight', 'vision_model.encoder.layers.13.mlp.fc1.weight', 'vision_model.encoder.layers.5.mlp.fc1.weight', 'vision_model.encoder.layers.10.self_attn.v_proj.weight', 'visual_projection.weight', 'vision_model.encoder.layers.1.mlp.fc2.weight', 'vision_model.post_layernorm.bias', 'vision_model.encoder.layers.3.self_attn.out_proj.weight', 'vision_model.embeddings.class_embedding', 'vision_model.encoder.layers.5.self_attn.v_proj.bias', 'vision_model.encoder.layers.18.layer_norm2.weight', 'vision_model.encoder.layers.0.layer_norm1.bias', 'vision_model.encoder.layers.1.self_attn.v_proj.bias', 'vision_model.encoder.layers.22.self_attn.v_proj.bias', 'vision_model.encoder.layers.23.self_attn.v_proj.weight', 'vision_model.encoder.layers.12.mlp.fc1.weight', 'vision_model.encoder.layers.19.mlp.fc1.bias', 'vision_model.encoder.layers.22.self_attn.out_proj.weight', 'vision_model.encoder.layers.5.self_attn.k_proj.weight', 'vision_model.encoder.layers.12.self_attn.v_proj.weight', 'vision_model.encoder.layers.1.layer_norm1.weight', 'vision_model.encoder.layers.4.self_attn.q_proj.weight', 'vision_model.encoder.layers.12.self_attn.q_proj.weight', 'vision_model.encoder.layers.9.layer_norm1.weight', 'vision_model.encoder.layers.15.mlp.fc2.bias', 'vision_model.encoder.layers.16.mlp.fc2.bias', 'vision_model.encoder.layers.14.mlp.fc2.bias', 'vision_model.encoder.layers.19.self_attn.v_proj.bias', 'vision_model.encoder.layers.2.self_attn.q_proj.bias', 'vision_model.encoder.layers.5.self_attn.k_proj.bias', 'vision_model.encoder.layers.12.self_attn.k_proj.weight', 'vision_model.encoder.layers.19.self_attn.out_proj.weight', 'vision_model.encoder.layers.19.self_attn.out_proj.bias', 'vision_model.encoder.layers.4.layer_norm2.weight', 'vision_model.encoder.layers.14.mlp.fc2.weight', 'vision_model.encoder.layers.12.mlp.fc2.bias', 'vision_model.post_layernorm.weight', 'vision_model.encoder.layers.0.mlp.fc2.weight', 'vision_model.encoder.layers.14.self_attn.k_proj.bias', 'vision_model.encoder.layers.1.mlp.fc1.weight', 'vision_model.encoder.layers.22.layer_norm1.weight', 'vision_model.encoder.layers.17.mlp.fc1.weight', 'vision_model.encoder.layers.9.mlp.fc1.weight', 'logit_scale', 'vision_model.encoder.layers.12.layer_norm2.weight', 'vision_model.encoder.layers.9.self_attn.out_proj.weight', 'vision_model.encoder.layers.11.layer_norm1.bias', 'vision_model.encoder.layers.16.mlp.fc1.weight', 'vision_model.encoder.layers.18.self_attn.q_proj.bias', 'vision_model.encoder.layers.23.layer_norm2.bias', 'vision_model.encoder.layers.17.self_attn.k_proj.bias', 'vision_model.encoder.layers.18.mlp.fc1.weight']
- This IS expected if you are initializing CLIPTextModel from the checkpoint of a model trained on another task or with another architecture (e.g. initializing a BertForSequenceClassification model from a BertForPreTraining model).
- This IS NOT expected if you are initializing CLIPTextModel from the checkpoint of a model that you expect to be exactly identical (initializing a BertForSequenceClassification model from a BertForSequenceClassification model).
/src/sample.py:354: DeprecationWarning: ANTIALIAS is deprecated and will be removed in Pillow 10 (2023-07-01). Use Resampling.LANCZOS instead.
  mask_image = mask_image.resize((input_image.shape[3],input_image.shape[2]), Image.ANTIALIAS)

  0%|          | 0/500 [00:00<?, ?it/s]
  0%|          | 1/500 [00:00<05:47,  1.44it/s]
  0%|          | 2/500 [00:01<04:35,  1.80it/s]
  1%|          | 3/500 [00:01<04:13,  1.96it/s]
  1%|          | 4/500 [00:01<02:55,  2.83it/s]
  1%|          | 5/500 [00:01<02:12,  3.74it/s]
  1%|          | 6/500 [00:01<01:46,  4.65it/s]
  1%|▏         | 7/500 [00:02<01:29,  5.49it/s]
  2%|▏         | 8/500 [00:02<01:19,  6.23it/s]
  2%|▏         | 9/500 [00:02<01:11,  6.83it/s]
  2%|▏         | 10/500 [00:02<01:06,  7.34it/s]
  2%|▏         | 11/500 [00:02<01:03,  7.73it/s]
  2%|▏         | 12/500 [00:02<01:00,  8.03it/s]
  3%|▎         | 13/500 [00:02<00:59,  8.24it/s]
  3%|▎         | 14/500 [00:02<00:57,  8.40it/s]
  3%|▎         | 15/500 [00:02<00:56,  8.51it/s]
  3%|▎         | 16/500 [00:03<00:56,  8.59it/s]
  3%|▎         | 17/500 [00:03<00:55,  8.65it/s]
  4%|▎         | 18/500 [00:03<00:55,  8.69it/s]
  4%|▍         | 19/500 [00:03<00:55,  8.69it/s]
  4%|▍         | 20/500 [00:03<00:55,  8.70it/s]
  4%|▍         | 21/500 [00:03<00:54,  8.73it/s]
  4%|▍         | 22/500 [00:03<00:54,  8.75it/s]
  5%|▍         | 23/500 [00:03<00:54,  8.76it/s]
  5%|▍         | 24/500 [00:04<00:54,  8.78it/s]
  5%|▌         | 25/500 [00:04<00:53,  8.80it/s]
  5%|▌         | 26/500 [00:04<01:26,  5.48it/s]
  5%|▌         | 27/500 [00:04<01:16,  6.17it/s]
  6%|▌         | 28/500 [00:04<01:09,  6.77it/s]
  6%|▌         | 29/500 [00:04<01:04,  7.28it/s]
  6%|▌         | 30/500 [00:04<01:01,  7.68it/s]
  6%|▌         | 31/500 [00:05<00:58,  7.99it/s]
  6%|▋         | 32/500 [00:05<00:56,  8.21it/s]
  7%|▋         | 33/500 [00:05<00:55,  8.39it/s]
  7%|▋         | 34/500 [00:05<00:54,  8.51it/s]
  7%|▋         | 35/500 [00:05<00:54,  8.60it/s]
  7%|▋         | 36/500 [00:05<00:53,  8.65it/s]
  7%|▋         | 37/500 [00:05<00:53,  8.70it/s]
  8%|▊         | 38/500 [00:05<00:53,  8.69it/s]
  8%|▊         | 39/500 [00:05<00:52,  8.70it/s]
  8%|▊         | 40/500 [00:06<00:52,  8.73it/s]
  8%|▊         | 41/500 [00:06<00:52,  8.76it/s]
  8%|▊         | 42/500 [00:06<00:52,  8.76it/s]
  9%|▊         | 43/500 [00:06<00:52,  8.77it/s]
  9%|▉         | 44/500 [00:06<00:52,  8.77it/s]
  9%|▉         | 45/500 [00:06<00:51,  8.76it/s]
  9%|▉         | 46/500 [00:06<00:51,  8.78it/s]
  9%|▉         | 47/500 [00:06<00:51,  8.80it/s]
 10%|▉         | 48/500 [00:06<00:51,  8.74it/s]
 10%|▉         | 49/500 [00:07<00:51,  8.74it/s]
 10%|█         | 50/500 [00:07<00:51,  8.75it/s]
 10%|█         | 51/500 [00:07<01:21,  5.54it/s]
 10%|█         | 52/500 [00:07<01:12,  6.22it/s]
 11%|█         | 53/500 [00:07<01:05,  6.81it/s]
 11%|█         | 54/500 [00:07<01:01,  7.30it/s]
 11%|█         | 55/500 [00:07<00:57,  7.70it/s]
 11%|█         | 56/500 [00:08<00:55,  7.98it/s]
 11%|█▏        | 57/500 [00:08<00:54,  8.20it/s]
 12%|█▏        | 58/500 [00:08<00:52,  8.39it/s]
 12%|█▏        | 59/500 [00:08<00:51,  8.49it/s]
 12%|█▏        | 60/500 [00:08<00:51,  8.59it/s]
 12%|█▏        | 61/500 [00:08<00:50,  8.65it/s]
 12%|█▏        | 62/500 [00:08<00:50,  8.70it/s]
 13%|█▎        | 63/500 [00:08<00:50,  8.74it/s]
 13%|█▎        | 64/500 [00:09<00:49,  8.75it/s]
 13%|█▎        | 65/500 [00:09<00:49,  8.77it/s]
 13%|█▎        | 66/500 [00:09<00:49,  8.78it/s]
 13%|█▎        | 67/500 [00:09<00:49,  8.75it/s]
 14%|█▎        | 68/500 [00:09<00:49,  8.75it/s]
 14%|█▍        | 69/500 [00:09<00:49,  8.75it/s]
 14%|█▍        | 70/500 [00:09<00:49,  8.75it/s]
 14%|█▍        | 71/500 [00:09<00:49,  8.75it/s]
 14%|█▍        | 72/500 [00:09<00:48,  8.77it/s]
 15%|█▍        | 73/500 [00:10<00:48,  8.79it/s]
 15%|█▍        | 74/500 [00:10<00:48,  8.80it/s]
 15%|█▌        | 75/500 [00:10<00:48,  8.78it/s]
 15%|█▌        | 76/500 [00:10<01:16,  5.53it/s]
 15%|█▌        | 77/500 [00:10<01:08,  6.21it/s]
 16%|█▌        | 78/500 [00:10<01:01,  6.81it/s]
 16%|█▌        | 79/500 [00:10<00:57,  7.31it/s]
 16%|█▌        | 80/500 [00:11<00:54,  7.71it/s]
 16%|█▌        | 81/500 [00:11<00:52,  8.00it/s]
 16%|█▋        | 82/500 [00:11<00:50,  8.22it/s]
 17%|█▋        | 83/500 [00:11<00:49,  8.37it/s]
 17%|█▋        | 84/500 [00:11<00:49,  8.49it/s]
 17%|█▋        | 85/500 [00:11<00:48,  8.56it/s]
 17%|█▋        | 86/500 [00:11<00:48,  8.61it/s]
 17%|█▋        | 87/500 [00:11<00:47,  8.65it/s]
 18%|█▊        | 88/500 [00:11<00:47,  8.69it/s]
 18%|█▊        | 89/500 [00:12<00:47,  8.71it/s]
 18%|█▊        | 90/500 [00:12<00:46,  8.74it/s]
 18%|█▊        | 91/500 [00:12<00:46,  8.74it/s]
 18%|█▊        | 92/500 [00:12<00:46,  8.75it/s]
 19%|█▊        | 93/500 [00:12<00:46,  8.75it/s]
 19%|█▉        | 94/500 [00:12<00:46,  8.76it/s]
 19%|█▉        | 95/500 [00:12<00:46,  8.74it/s]
 19%|█▉        | 96/500 [00:12<00:46,  8.75it/s]
 19%|█▉        | 97/500 [00:12<00:46,  8.76it/s]
 20%|█▉        | 98/500 [00:13<00:45,  8.78it/s]
 20%|█▉        | 99/500 [00:13<00:45,  8.80it/s]
 20%|██        | 100/500 [00:13<00:45,  8.79it/s]
 20%|██        | 101/500 [00:13<01:11,  5.56it/s]
 20%|██        | 102/500 [00:13<01:05,  6.12it/s]
 21%|██        | 103/500 [00:13<00:59,  6.72it/s]
 21%|██        | 104/500 [00:14<00:54,  7.23it/s]
 21%|██        | 105/500 [00:14<00:51,  7.65it/s]
 21%|██        | 106/500 [00:14<00:49,  7.94it/s]
 21%|██▏       | 107/500 [00:14<00:48,  8.18it/s]
 22%|██▏       | 108/500 [00:14<00:46,  8.35it/s]
 22%|██▏       | 109/500 [00:14<00:46,  8.46it/s]
 22%|██▏       | 110/500 [00:14<00:45,  8.55it/s]
 22%|██▏       | 111/500 [00:14<00:45,  8.60it/s]
 22%|██▏       | 112/500 [00:14<00:44,  8.64it/s]
 23%|██▎       | 113/500 [00:15<00:44,  8.66it/s]
 23%|██▎       | 114/500 [00:15<00:44,  8.69it/s]
 23%|██▎       | 115/500 [00:15<00:44,  8.72it/s]
 23%|██▎       | 116/500 [00:15<00:43,  8.73it/s]
 23%|██▎       | 117/500 [00:15<00:43,  8.74it/s]
 24%|██▎       | 118/500 [00:15<00:43,  8.76it/s]
 24%|██▍       | 119/500 [00:15<00:43,  8.77it/s]
 24%|██▍       | 120/500 [00:15<00:44,  8.51it/s]
 24%|██▍       | 121/500 [00:15<00:44,  8.59it/s]
 24%|██▍       | 122/500 [00:16<00:43,  8.66it/s]
 25%|██▍       | 123/500 [00:16<00:43,  8.72it/s]
 25%|██▍       | 124/500 [00:16<00:42,  8.75it/s]
 25%|██▌       | 125/500 [00:16<00:42,  8.76it/s]
 25%|██▌       | 126/500 [00:16<01:06,  5.62it/s]
 25%|██▌       | 127/500 [00:16<00:59,  6.30it/s]
 26%|██▌       | 128/500 [00:16<00:54,  6.88it/s]
 26%|██▌       | 129/500 [00:17<00:50,  7.32it/s]
 26%|██▌       | 130/500 [00:17<00:48,  7.70it/s]
 26%|██▌       | 131/500 [00:17<00:46,  7.99it/s]
 26%|██▋       | 132/500 [00:17<00:44,  8.21it/s]
 27%|██▋       | 133/500 [00:17<00:43,  8.36it/s]
 27%|██▋       | 134/500 [00:17<00:43,  8.48it/s]
 27%|██▋       | 135/500 [00:17<00:42,  8.56it/s]
 27%|██▋       | 136/500 [00:17<00:42,  8.62it/s]
 27%|██▋       | 137/500 [00:18<00:41,  8.67it/s]
 28%|██▊       | 138/500 [00:18<00:41,  8.70it/s]
 28%|██▊       | 139/500 [00:18<00:41,  8.72it/s]
 28%|██▊       | 140/500 [00:18<00:41,  8.74it/s]
 28%|██▊       | 141/500 [00:18<00:41,  8.74it/s]
 28%|██▊       | 142/500 [00:18<00:40,  8.76it/s]
 29%|██▊       | 143/500 [00:18<00:40,  8.75it/s]
 29%|██▉       | 144/500 [00:18<00:40,  8.76it/s]
 29%|██▉       | 145/500 [00:18<00:40,  8.76it/s]
 29%|██▉       | 146/500 [00:19<00:40,  8.78it/s]
 29%|██▉       | 147/500 [00:19<00:40,  8.78it/s]
 30%|██▉       | 148/500 [00:19<00:40,  8.77it/s]
 30%|██▉       | 149/500 [00:19<00:40,  8.76it/s]
 30%|███       | 150/500 [00:19<00:39,  8.77it/s]
 30%|███       | 151/500 [00:19<01:01,  5.69it/s]
 30%|███       | 152/500 [00:19<00:54,  6.36it/s]
 31%|███       | 153/500 [00:20<00:50,  6.92it/s]
 31%|███       | 154/500 [00:20<00:46,  7.39it/s]
 31%|███       | 155/500 [00:20<00:44,  7.74it/s]
 31%|███       | 156/500 [00:20<00:42,  8.02it/s]
 31%|███▏      | 157/500 [00:20<00:41,  8.23it/s]
 32%|███▏      | 158/500 [00:20<00:40,  8.41it/s]
 32%|███▏      | 159/500 [00:20<00:39,  8.53it/s]
 32%|███▏      | 160/500 [00:20<00:39,  8.60it/s]
 32%|███▏      | 161/500 [00:20<00:39,  8.64it/s]
 32%|███▏      | 162/500 [00:21<00:38,  8.69it/s]
 33%|███▎      | 163/500 [00:21<00:38,  8.72it/s]
 33%|███▎      | 164/500 [00:21<00:38,  8.73it/s]
 33%|███▎      | 165/500 [00:21<00:38,  8.74it/s]
 33%|███▎      | 166/500 [00:21<00:38,  8.75it/s]
 33%|███▎      | 167/500 [00:21<00:37,  8.77it/s]
 34%|███▎      | 168/500 [00:21<00:37,  8.79it/s]
 34%|███▍      | 169/500 [00:21<00:37,  8.78it/s]
 34%|███▍      | 170/500 [00:21<00:37,  8.78it/s]
 34%|███▍      | 171/500 [00:22<00:37,  8.78it/s]
 34%|███▍      | 172/500 [00:22<00:37,  8.77it/s]
 35%|███▍      | 173/500 [00:22<00:37,  8.76it/s]
 35%|███▍      | 174/500 [00:22<00:37,  8.76it/s]
 35%|███▌      | 175/500 [00:22<00:37,  8.76it/s]
 35%|███▌      | 176/500 [00:22<00:57,  5.64it/s]
 35%|███▌      | 177/500 [00:22<00:51,  6.22it/s]
 36%|███▌      | 178/500 [00:23<00:47,  6.81it/s]
 36%|███▌      | 179/500 [00:23<00:44,  7.28it/s]
 36%|███▌      | 180/500 [00:23<00:41,  7.68it/s]
 36%|███▌      | 181/500 [00:23<00:39,  7.99it/s]
 36%|███▋      | 182/500 [00:23<00:38,  8.21it/s]
 37%|███▋      | 183/500 [00:23<00:37,  8.38it/s]
 37%|███▋      | 184/500 [00:23<00:37,  8.49it/s]
 37%|███▋      | 185/500 [00:23<00:36,  8.56it/s]
 37%|███▋      | 186/500 [00:24<00:36,  8.63it/s]
 37%|███▋      | 187/500 [00:24<00:36,  8.65it/s]
 38%|███▊      | 188/500 [00:24<00:35,  8.68it/s]
 38%|███▊      | 189/500 [00:24<00:35,  8.71it/s]
 38%|███▊      | 190/500 [00:24<00:35,  8.75it/s]
 38%|███▊      | 191/500 [00:24<00:35,  8.77it/s]
 38%|███▊      | 192/500 [00:24<00:35,  8.79it/s]
 39%|███▊      | 193/500 [00:24<00:34,  8.78it/s]
 39%|███▉      | 194/500 [00:24<00:34,  8.77it/s]
 39%|███▉      | 195/500 [00:25<00:34,  8.76it/s]
 39%|███▉      | 196/500 [00:25<00:34,  8.77it/s]
 39%|███▉      | 197/500 [00:25<00:34,  8.77it/s]
 40%|███▉      | 198/500 [00:25<00:34,  8.76it/s]
 40%|███▉      | 199/500 [00:25<00:34,  8.78it/s]
 40%|████      | 200/500 [00:25<00:34,  8.78it/s]
 40%|████      | 201/500 [00:25<00:55,  5.35it/s]
 40%|████      | 202/500 [00:26<00:49,  6.05it/s]
 41%|████      | 203/500 [00:26<00:44,  6.68it/s]
 41%|████      | 204/500 [00:26<00:41,  7.21it/s]
 41%|████      | 205/500 [00:26<00:38,  7.63it/s]
 41%|████      | 206/500 [00:26<00:36,  7.96it/s]
 41%|████▏     | 207/500 [00:26<00:35,  8.20it/s]
 42%|████▏     | 208/500 [00:26<00:34,  8.38it/s]
 42%|████▏     | 209/500 [00:26<00:34,  8.51it/s]
 42%|████▏     | 210/500 [00:26<00:33,  8.61it/s]
 42%|████▏     | 211/500 [00:27<00:33,  8.67it/s]
 42%|████▏     | 212/500 [00:27<00:33,  8.72it/s]
 43%|████▎     | 213/500 [00:27<00:32,  8.75it/s]
 43%|████▎     | 214/500 [00:27<00:32,  8.78it/s]
 43%|████▎     | 215/500 [00:27<00:32,  8.80it/s]
 43%|████▎     | 216/500 [00:27<00:32,  8.81it/s]
 43%|████▎     | 217/500 [00:27<00:32,  8.83it/s]
 44%|████▎     | 218/500 [00:27<00:31,  8.84it/s]
 44%|████▍     | 219/500 [00:28<00:31,  8.84it/s]
 44%|████▍     | 220/500 [00:28<00:31,  8.85it/s]
 44%|████▍     | 221/500 [00:28<00:31,  8.85it/s]
 44%|████▍     | 222/500 [00:28<00:31,  8.85it/s]
 45%|████▍     | 223/500 [00:28<00:31,  8.85it/s]
 45%|████▍     | 224/500 [00:28<00:31,  8.85it/s]
 45%|████▌     | 225/500 [00:28<00:31,  8.85it/s]
 45%|████▌     | 226/500 [00:28<00:46,  5.89it/s]
 45%|████▌     | 227/500 [00:29<00:41,  6.54it/s]
 46%|████▌     | 228/500 [00:29<00:38,  7.09it/s]
 46%|████▌     | 229/500 [00:29<00:35,  7.55it/s]
 46%|████▌     | 230/500 [00:29<00:34,  7.90it/s]
 46%|████▌     | 231/500 [00:29<00:32,  8.15it/s]
 46%|████▋     | 232/500 [00:29<00:32,  8.35it/s]
 47%|████▋     | 233/500 [00:29<00:31,  8.50it/s]
 47%|████▋     | 234/500 [00:29<00:30,  8.60it/s]
 47%|████▋     | 235/500 [00:30<00:30,  8.67it/s]
 47%|████▋     | 236/500 [00:30<00:30,  8.72it/s]
 47%|████▋     | 237/500 [00:30<00:30,  8.75it/s]
 48%|████▊     | 238/500 [00:30<00:29,  8.76it/s]
 48%|████▊     | 239/500 [00:30<00:29,  8.78it/s]
 48%|████▊     | 240/500 [00:30<00:29,  8.80it/s]
 48%|████▊     | 241/500 [00:30<00:29,  8.81it/s]
 48%|████▊     | 242/500 [00:30<00:29,  8.83it/s]
 49%|████▊     | 243/500 [00:30<00:29,  8.84it/s]
 49%|████▉     | 244/500 [00:31<00:28,  8.84it/s]
 49%|████▉     | 245/500 [00:31<00:28,  8.84it/s]
 49%|████▉     | 246/500 [00:31<00:28,  8.83it/s]
 49%|████▉     | 247/500 [00:31<00:28,  8.83it/s]
 50%|████▉     | 248/500 [00:31<00:28,  8.83it/s]
 50%|████▉     | 249/500 [00:31<00:28,  8.83it/s]
 50%|█████     | 250/500 [00:31<00:28,  8.84it/s]
 50%|█████     | 251/500 [00:32<00:41,  5.95it/s]
 50%|█████     | 252/500 [00:32<00:37,  6.59it/s]
 51%|█████     | 253/500 [00:32<00:34,  7.13it/s]
 51%|█████     | 254/500 [00:32<00:32,  7.57it/s]
 51%|█████     | 255/500 [00:32<00:30,  7.91it/s]
 51%|█████     | 256/500 [00:32<00:29,  8.17it/s]
 51%|█████▏    | 257/500 [00:32<00:29,  8.36it/s]
 52%|█████▏    | 258/500 [00:32<00:28,  8.49it/s]
 52%|█████▏    | 259/500 [00:32<00:28,  8.59it/s]
 52%|█████▏    | 260/500 [00:33<00:27,  8.67it/s]
 52%|█████▏    | 261/500 [00:33<00:27,  8.71it/s]
 52%|█████▏    | 262/500 [00:33<00:27,  8.74it/s]
 53%|█████▎    | 263/500 [00:33<00:27,  8.76it/s]
 53%|█████▎    | 264/500 [00:33<00:26,  8.78it/s]
 53%|█████▎    | 265/500 [00:33<00:26,  8.79it/s]
 53%|█████▎    | 266/500 [00:33<00:26,  8.80it/s]
 53%|█████▎    | 267/500 [00:33<00:26,  8.81it/s]
 54%|█████▎    | 268/500 [00:33<00:26,  8.81it/s]
 54%|█████▍    | 269/500 [00:34<00:26,  8.82it/s]
 54%|█████▍    | 270/500 [00:34<00:26,  8.82it/s]
 54%|█████▍    | 271/500 [00:34<00:25,  8.83it/s]
 54%|█████▍    | 272/500 [00:34<00:25,  8.84it/s]
 55%|█████▍    | 273/500 [00:34<00:25,  8.83it/s]
 55%|█████▍    | 274/500 [00:34<00:25,  8.83it/s]
 55%|█████▌    | 275/500 [00:34<00:25,  8.84it/s]
 55%|█████▌    | 276/500 [00:35<00:42,  5.26it/s]
 55%|█████▌    | 277/500 [00:35<00:37,  5.97it/s]
 56%|█████▌    | 278/500 [00:35<00:33,  6.62it/s]
 56%|█████▌    | 279/500 [00:35<00:30,  7.15it/s]
 56%|█████▌    | 280/500 [00:35<00:29,  7.58it/s]
 56%|█████▌    | 281/500 [00:35<00:27,  7.92it/s]
 56%|█████▋    | 282/500 [00:35<00:26,  8.17it/s]
 57%|█████▋    | 283/500 [00:35<00:25,  8.36it/s]
 57%|█████▋    | 284/500 [00:35<00:25,  8.49it/s]
 57%|█████▋    | 285/500 [00:36<00:25,  8.59it/s]
 57%|█████▋    | 286/500 [00:36<00:24,  8.66it/s]
 57%|█████▋    | 287/500 [00:36<00:24,  8.72it/s]
 58%|█████▊    | 288/500 [00:36<00:24,  8.75it/s]
 58%|█████▊    | 289/500 [00:36<00:24,  8.77it/s]
 58%|█████▊    | 290/500 [00:36<00:23,  8.80it/s]
 58%|█████▊    | 291/500 [00:36<00:23,  8.81it/s]
 58%|█████▊    | 292/500 [00:36<00:23,  8.81it/s]
 59%|█████▊    | 293/500 [00:37<00:23,  8.82it/s]
 59%|█████▉    | 294/500 [00:37<00:23,  8.82it/s]
 59%|█████▉    | 295/500 [00:37<00:23,  8.81it/s]
 59%|█████▉    | 296/500 [00:37<00:23,  8.81it/s]
 59%|█████▉    | 297/500 [00:37<00:23,  8.82it/s]
 60%|█████▉    | 298/500 [00:37<00:22,  8.81it/s]
 60%|█████▉    | 299/500 [00:37<00:22,  8.80it/s]
 60%|██████    | 300/500 [00:37<00:22,  8.81it/s]
 60%|██████    | 301/500 [00:38<00:39,  5.00it/s]
 60%|██████    | 302/500 [00:38<00:34,  5.73it/s]
 61%|██████    | 303/500 [00:38<00:30,  6.41it/s]
 61%|██████    | 304/500 [00:38<00:28,  6.99it/s]
 61%|██████    | 305/500 [00:38<00:26,  7.46it/s]
 61%|██████    | 306/500 [00:38<00:24,  7.83it/s]
 61%|██████▏   | 307/500 [00:38<00:23,  8.11it/s]
 62%|██████▏   | 308/500 [00:39<00:23,  8.32it/s]
 62%|██████▏   | 309/500 [00:39<00:22,  8.47it/s]
 62%|██████▏   | 310/500 [00:39<00:22,  8.58it/s]
 62%|██████▏   | 311/500 [00:39<00:21,  8.65it/s]
 62%|██████▏   | 312/500 [00:39<00:21,  8.71it/s]
 63%|██████▎   | 313/500 [00:39<00:21,  8.75it/s]
 63%|██████▎   | 314/500 [00:39<00:21,  8.77it/s]
 63%|██████▎   | 315/500 [00:39<00:21,  8.79it/s]
 63%|██████▎   | 316/500 [00:39<00:20,  8.81it/s]
 63%|██████▎   | 317/500 [00:40<00:20,  8.82it/s]
 64%|██████▎   | 318/500 [00:40<00:20,  8.83it/s]
 64%|██████▍   | 319/500 [00:40<00:20,  8.84it/s]
 64%|██████▍   | 320/500 [00:40<00:20,  8.85it/s]
 64%|██████▍   | 321/500 [00:40<00:20,  8.85it/s]
 64%|██████▍   | 322/500 [00:40<00:20,  8.85it/s]
 65%|██████▍   | 323/500 [00:40<00:19,  8.85it/s]
 65%|██████▍   | 324/500 [00:40<00:19,  8.85it/s]
 65%|██████▌   | 325/500 [00:40<00:19,  8.85it/s]
 65%|██████▌   | 326/500 [00:41<00:36,  4.73it/s]
 65%|██████▌   | 327/500 [00:41<00:31,  5.49it/s]
 66%|██████▌   | 328/500 [00:41<00:27,  6.20it/s]
 66%|██████▌   | 329/500 [00:41<00:25,  6.80it/s]
 66%|██████▌   | 330/500 [00:41<00:23,  7.31it/s]
 66%|██████▌   | 331/500 [00:41<00:21,  7.71it/s]
 66%|██████▋   | 332/500 [00:42<00:20,  8.01it/s]
 67%|██████▋   | 333/500 [00:42<00:20,  8.24it/s]
 67%|██████▋   | 334/500 [00:42<00:19,  8.41it/s]
 67%|██████▋   | 335/500 [00:42<00:19,  8.54it/s]
 67%|██████▋   | 336/500 [00:42<00:19,  8.63it/s]
 67%|██████▋   | 337/500 [00:42<00:18,  8.69it/s]
 68%|██████▊   | 338/500 [00:42<00:18,  8.73it/s]
 68%|██████▊   | 339/500 [00:42<00:18,  8.77it/s]
 68%|██████▊   | 340/500 [00:42<00:18,  8.79it/s]
 68%|██████▊   | 341/500 [00:43<00:18,  8.80it/s]
 68%|██████▊   | 342/500 [00:43<00:17,  8.81it/s]
 69%|██████▊   | 343/500 [00:43<00:17,  8.82it/s]
 69%|██████▉   | 344/500 [00:43<00:17,  8.83it/s]
 69%|██████▉   | 345/500 [00:43<00:17,  8.84it/s]
 69%|██████▉   | 346/500 [00:43<00:17,  8.84it/s]
 69%|██████▉   | 347/500 [00:43<00:17,  8.84it/s]
 70%|██████▉   | 348/500 [00:43<00:17,  8.84it/s]
 70%|██████▉   | 349/500 [00:43<00:17,  8.84it/s]
 70%|███████   | 350/500 [00:44<00:16,  8.84it/s]
 70%|███████   | 351/500 [00:44<00:30,  4.93it/s]
 70%|███████   | 352/500 [00:44<00:26,  5.67it/s]
 71%|███████   | 353/500 [00:44<00:23,  6.36it/s]
 71%|███████   | 354/500 [00:44<00:21,  6.94it/s]
 71%|███████   | 355/500 [00:44<00:19,  7.42it/s]
 71%|███████   | 356/500 [00:45<00:18,  7.80it/s]
 71%|███████▏  | 357/500 [00:45<00:17,  8.08it/s]
 72%|███████▏  | 358/500 [00:45<00:17,  8.29it/s]
 72%|███████▏  | 359/500 [00:45<00:16,  8.45it/s]
 72%|███████▏  | 360/500 [00:45<00:16,  8.56it/s]
 72%|███████▏  | 361/500 [00:45<00:16,  8.65it/s]
 72%|███████▏  | 362/500 [00:45<00:15,  8.70it/s]
 73%|███████▎  | 363/500 [00:45<00:15,  8.73it/s]
 73%|███████▎  | 364/500 [00:45<00:15,  8.76it/s]
 73%|███████▎  | 365/500 [00:46<00:15,  8.79it/s]
 73%|███████▎  | 366/500 [00:46<00:15,  8.80it/s]
 73%|███████▎  | 367/500 [00:46<00:15,  8.81it/s]
 74%|███████▎  | 368/500 [00:46<00:14,  8.82it/s]
 74%|███████▍  | 369/500 [00:46<00:14,  8.83it/s]
 74%|███████▍  | 370/500 [00:46<00:14,  8.83it/s]
 74%|███████▍  | 371/500 [00:46<00:14,  8.83it/s]
 74%|███████▍  | 372/500 [00:46<00:14,  8.83it/s]
 75%|███████▍  | 373/500 [00:46<00:14,  8.82it/s]
 75%|███████▍  | 374/500 [00:47<00:14,  8.83it/s]
 75%|███████▌  | 375/500 [00:47<00:14,  8.83it/s]
 75%|███████▌  | 376/500 [00:47<00:25,  4.90it/s]
 75%|███████▌  | 377/500 [00:47<00:21,  5.65it/s]
 76%|███████▌  | 378/500 [00:47<00:19,  6.33it/s]
 76%|███████▌  | 379/500 [00:47<00:17,  6.92it/s]
 76%|███████▌  | 380/500 [00:48<00:16,  7.41it/s]
 76%|███████▌  | 381/500 [00:48<00:15,  7.79it/s]
 76%|███████▋  | 382/500 [00:48<00:14,  8.08it/s]
 77%|███████▋  | 383/500 [00:48<00:14,  8.29it/s]
 77%|███████▋  | 384/500 [00:48<00:13,  8.41it/s]
 77%|███████▋  | 385/500 [00:48<00:13,  8.54it/s]
 77%|███████▋  | 386/500 [00:48<00:13,  8.63it/s]
 77%|███████▋  | 387/500 [00:48<00:12,  8.69it/s]
 78%|███████▊  | 388/500 [00:48<00:12,  8.74it/s]
 78%|███████▊  | 389/500 [00:49<00:12,  8.77it/s]
 78%|███████▊  | 390/500 [00:49<00:12,  8.80it/s]
 78%|███████▊  | 391/500 [00:49<00:12,  8.82it/s]
 78%|███████▊  | 392/500 [00:49<00:12,  8.84it/s]
 79%|███████▊  | 393/500 [00:49<00:12,  8.84it/s]
 79%|███████▉  | 394/500 [00:49<00:11,  8.85it/s]
 79%|███████▉  | 395/500 [00:49<00:11,  8.86it/s]
 79%|███████▉  | 396/500 [00:49<00:11,  8.86it/s]
 79%|███████▉  | 397/500 [00:50<00:11,  8.86it/s]
 80%|███████▉  | 398/500 [00:50<00:11,  8.86it/s]
 80%|███████▉  | 399/500 [00:50<00:11,  8.85it/s]
 80%|████████  | 400/500 [00:50<00:11,  8.85it/s]
 80%|████████  | 401/500 [00:50<00:16,  6.16it/s]
 80%|████████  | 402/500 [00:50<00:14,  6.77it/s]
 81%|████████  | 403/500 [00:50<00:13,  7.29it/s]
 81%|████████  | 404/500 [00:50<00:12,  7.70it/s]
 81%|████████  | 405/500 [00:51<00:11,  8.02it/s]
 81%|████████  | 406/500 [00:51<00:11,  8.25it/s]
 81%|████████▏ | 407/500 [00:51<00:11,  8.42it/s]
 82%|████████▏ | 408/500 [00:51<00:10,  8.55it/s]
 82%|████████▏ | 409/500 [00:51<00:10,  8.63it/s]
 82%|████████▏ | 410/500 [00:51<00:10,  8.69it/s]
 82%|████████▏ | 411/500 [00:51<00:10,  8.74it/s]
 82%|████████▏ | 412/500 [00:51<00:10,  8.78it/s]
 83%|████████▎ | 413/500 [00:51<00:09,  8.80it/s]
 83%|████████▎ | 414/500 [00:52<00:09,  8.82it/s]
 83%|████████▎ | 415/500 [00:52<00:09,  8.83it/s]
 83%|████████▎ | 416/500 [00:52<00:09,  8.84it/s]
 83%|████████▎ | 417/500 [00:52<00:09,  8.85it/s]
 84%|████████▎ | 418/500 [00:52<00:09,  8.85it/s]
 84%|████████▍ | 419/500 [00:52<00:09,  8.86it/s]
 84%|████████▍ | 420/500 [00:52<00:09,  8.86it/s]
 84%|████████▍ | 421/500 [00:52<00:08,  8.86it/s]
 84%|████████▍ | 422/500 [00:52<00:08,  8.84it/s]
 85%|████████▍ | 423/500 [00:53<00:08,  8.84it/s]
 85%|████████▍ | 424/500 [00:53<00:08,  8.84it/s]
 85%|████████▌ | 425/500 [00:53<00:08,  8.84it/s]
 85%|████████▌ | 426/500 [00:53<00:13,  5.46it/s]
 85%|████████▌ | 427/500 [00:53<00:11,  6.16it/s]
 86%|████████▌ | 428/500 [00:53<00:10,  6.77it/s]
 86%|████████▌ | 429/500 [00:54<00:09,  7.29it/s]
 86%|████████▌ | 430/500 [00:54<00:09,  7.69it/s]
 86%|████████▌ | 431/500 [00:54<00:08,  8.01it/s]
 86%|████████▋ | 432/500 [00:54<00:08,  8.24it/s]
 87%|████████▋ | 433/500 [00:54<00:07,  8.41it/s]
 87%|████████▋ | 434/500 [00:54<00:07,  8.53it/s]
 87%|████████▋ | 435/500 [00:54<00:07,  8.62it/s]
 87%|████████▋ | 436/500 [00:54<00:07,  8.68it/s]
 87%|████████▋ | 437/500 [00:54<00:07,  8.73it/s]
 88%|████████▊ | 438/500 [00:55<00:07,  8.77it/s]
 88%|████████▊ | 439/500 [00:55<00:06,  8.79it/s]
 88%|████████▊ | 440/500 [00:55<00:06,  8.80it/s]
 88%|████████▊ | 441/500 [00:55<00:06,  8.80it/s]
 88%|████████▊ | 442/500 [00:55<00:06,  8.80it/s]
 89%|████████▊ | 443/500 [00:55<00:06,  8.81it/s]
 89%|████████▉ | 444/500 [00:55<00:06,  8.81it/s]
 89%|████████▉ | 445/500 [00:55<00:06,  8.80it/s]
 89%|████████▉ | 446/500 [00:55<00:06,  8.82it/s]
 89%|████████▉ | 447/500 [00:56<00:06,  8.83it/s]
 90%|████████▉ | 448/500 [00:56<00:05,  8.84it/s]
 90%|████████▉ | 449/500 [00:56<00:05,  8.85it/s]
 90%|█████████ | 450/500 [00:56<00:05,  8.86it/s]
 90%|█████████ | 451/500 [00:56<00:07,  6.21it/s]
 90%|█████████ | 452/500 [00:56<00:07,  6.81it/s]
 91%|█████████ | 453/500 [00:56<00:06,  7.32it/s]
 91%|█████████ | 454/500 [00:57<00:05,  7.73it/s]
 91%|█████████ | 455/500 [00:57<00:05,  8.03it/s]
 91%|█████████ | 456/500 [00:57<00:05,  8.26it/s]
 91%|█████████▏| 457/500 [00:57<00:05,  8.43it/s]
 92%|█████████▏| 458/500 [00:57<00:04,  8.55it/s]
 92%|█████████▏| 459/500 [00:57<00:04,  8.64it/s]
 92%|█████████▏| 460/500 [00:57<00:04,  8.71it/s]
 92%|█████████▏| 461/500 [00:57<00:04,  8.75it/s]
 92%|█████████▏| 462/500 [00:57<00:04,  8.78it/s]
 93%|█████████▎| 463/500 [00:58<00:04,  8.81it/s]
 93%|█████████▎| 464/500 [00:58<00:04,  8.82it/s]
 93%|█████████▎| 465/500 [00:58<00:03,  8.82it/s]
 93%|█████████▎| 466/500 [00:58<00:03,  8.82it/s]
 93%|█████████▎| 467/500 [00:58<00:03,  8.81it/s]
 94%|█████████▎| 468/500 [00:58<00:03,  8.83it/s]
 94%|█████████▍| 469/500 [00:58<00:03,  8.83it/s]
 94%|█████████▍| 470/500 [00:58<00:03,  8.83it/s]
 94%|█████████▍| 471/500 [00:58<00:03,  8.83it/s]
 94%|█████████▍| 472/500 [00:59<00:03,  8.83it/s]
 95%|█████████▍| 473/500 [00:59<00:03,  8.84it/s]
 95%|█████████▍| 474/500 [00:59<00:02,  8.85it/s]
 95%|█████████▌| 475/500 [00:59<00:02,  8.85it/s]
 95%|█████████▌| 476/500 [00:59<00:03,  6.22it/s]
 95%|█████████▌| 477/500 [00:59<00:03,  6.82it/s]
 96%|█████████▌| 478/500 [00:59<00:03,  7.32it/s]
 96%|█████████▌| 479/500 [00:59<00:02,  7.72it/s]
 96%|█████████▌| 480/500 [01:00<00:02,  8.02it/s]
 96%|█████████▌| 481/500 [01:00<00:02,  8.25it/s]
 96%|█████████▋| 482/500 [01:00<00:02,  8.43it/s]
 97%|█████████▋| 483/500 [01:00<00:01,  8.55it/s]
 97%|█████████▋| 484/500 [01:00<00:01,  8.64it/s]
 97%|█████████▋| 485/500 [01:00<00:01,  8.71it/s]
 97%|█████████▋| 486/500 [01:00<00:01,  8.75it/s]
 97%|█████████▋| 487/500 [01:00<00:01,  8.78it/s]
 98%|█████████▊| 488/500 [01:01<00:01,  8.81it/s]
 98%|█████████▊| 489/500 [01:01<00:01,  8.83it/s]
 98%|█████████▊| 490/500 [01:01<00:01,  8.84it/s]
 98%|█████████▊| 491/500 [01:01<00:01,  8.85it/s]
 98%|█████████▊| 492/500 [01:01<00:00,  8.84it/s]
 99%|█████████▊| 493/500 [01:01<00:00,  8.84it/s]
 99%|█████████▉| 494/500 [01:01<00:00,  8.84it/s]
 99%|█████████▉| 495/500 [01:01<00:00,  8.83it/s]
 99%|█████████▉| 496/500 [01:01<00:00,  8.83it/s]
 99%|█████████▉| 497/500 [01:02<00:00,  8.84it/s]
100%|█████████▉| 498/500 [01:02<00:00,  8.84it/s]
100%|█████████▉| 499/500 [01:02<00:00,  8.84it/s]
100%|██████████| 500/500 [01:02<00:00,  8.84it/s]
100%|██████████| 500/500 [01:02<00:00,  8.02it/s]

This example was created by a different version, devxpy/glid-3-xl-stable:760f4043.

Examples

View more examples

Run time and cost

This model costs approximately $0.13 to run on Replicate, or 7 runs per $1, but this varies depending on your inputs. It is also open source and you can run it on your own computer with Docker.

This model runs on Nvidia A100 (80GB) GPU hardware. Predictions typically complete within 92 seconds. The predict time for this model varies significantly based on the inputs.

Readme

This model doesn't have a readme.