fofr/ays-text-to-image:a004c3ac – Run with an API on Replicate

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fofr /ays-text-to-image:a004c3ac

Playground API

Input

prompt

string

Shift + Return to add a new line

Default: "a photo of an astronaut riding a unicorn"

negative_prompt

string

Shift + Return to add a new line

The negative prompt to guide image generation.

Default: ""

checkpoint

string

The SDXL model to use for generation

Default: "albedobaseXL_v21.safetensors"

width

integer

Default: 1024

height

integer

Default: 1024

num_outputs

integer

(minimum: 1, maximum: 10)

Number of outputs

Default: 1

sampler_name

string

An enumeration.

Default: "euler"

guidance_scale

number

(minimum: 0, maximum: 30)

Scale for classifier-free guidance

Default: 7.5

steps

integer

(minimum: 10, maximum: 100)

Number of diffusion steps. (A minimum of 10 with AYS)

Default: 10

seed

integer

output_format

string

Format of the output images

Default: "webp"

output_quality

integer

(minimum: 0, maximum: 100)

Quality of the output images, from 0 to 100. 100 is best quality, 0 is lowest quality.

Default: 80

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

npx create-replicate --model=fofr/ays-text-to-image

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 fofr/ays-text-to-image using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

const output = await replicate.run(
  "fofr/ays-text-to-image:a004c3ac8f62ac95a90b5a0c264beb47b66a6d1f8141b76fb27cd90e9a8bfe8e",
  {
    input: {
      steps: 10,
      width: 1156,
      height: 768,
      prompt: "a photo of some steps",
      checkpoint: "ProteusV0.4.safetensors",
      num_outputs: 1,
      sampler_name: "euler",
      output_format: "webp",
      guidance_scale: 7.5,
      output_quality: 80,
      negative_prompt: ""
    }
  }
);
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 fofr/ays-text-to-image using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

output = replicate.run(
    "fofr/ays-text-to-image:a004c3ac8f62ac95a90b5a0c264beb47b66a6d1f8141b76fb27cd90e9a8bfe8e",
    input={
        "steps": 10,
        "width": 1156,
        "height": 768,
        "prompt": "a photo of some steps",
        "checkpoint": "ProteusV0.4.safetensors",
        "num_outputs": 1,
        "sampler_name": "euler",
        "output_format": "webp",
        "guidance_scale": 7.5,
        "output_quality": 80,
        "negative_prompt": ""
    }
)
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 fofr/ays-text-to-image 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": "a004c3ac8f62ac95a90b5a0c264beb47b66a6d1f8141b76fb27cd90e9a8bfe8e",
    "input": {
      "steps": 10,
      "width": 1156,
      "height": 768,
      "prompt": "a photo of some steps",
      "checkpoint": "ProteusV0.4.safetensors",
      "num_outputs": 1,
      "sampler_name": "euler",
      "output_format": "webp",
      "guidance_scale": 7.5,
      "output_quality": 80,
      "negative_prompt": ""
    }
  }' \
  https://api.replicate.com/v1/predictions

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

Output

{
  "completed_at": "2024-04-30T11:57:02.551140Z",
  "created_at": "2024-04-30T11:56:50.121000Z",
  "data_removed": false,
  "error": null,
  "id": "5enrvraw95rgm0cf5veva7rggm",
  "input": {
    "steps": 10,
    "width": 1156,
    "height": 768,
    "prompt": "a photo of some steps",
    "checkpoint": "ProteusV0.4.safetensors",
    "num_outputs": 1,
    "sampler_name": "euler",
    "output_format": "webp",
    "guidance_scale": 7.5,
    "output_quality": 80,
    "negative_prompt": ""
  },
  "logs": "Random seed set to: 2615771573\nChecking inputs\n====================================\nChecking weights\n⏳ Downloading ProteusV0.4.safetensors to ComfyUI/models/checkpoints\n⌛️ Downloaded ProteusV0.4.safetensors in 7.46s, size: 6617.77MB\n✅ ProteusV0.4.safetensors\n====================================\nRunning workflow\ngot prompt\nExecuting node 4, title: Load Checkpoint, class type: CheckpointLoaderSimple\nmodel_type EPS\nUsing pytorch attention in VAE\nUsing pytorch attention in VAE\nclip missing: ['clip_l.logit_scale', 'clip_l.transformer.text_projection.weight']\nloaded straight to GPU\nRequested to load SDXL\nLoading 1 new model\nExecuting node 6, title: CLIP Text Encode (Prompt), class type: CLIPTextEncode\nRequested to load SDXLClipModel\nLoading 1 new model\nExecuting node 19, title: CLIP Text Encode (Prompt), class type: CLIPTextEncode\nExecuting node 21, title: SamplerCustom, class type: SamplerCustom\n  0%|          | 0/10 [00:00<?, ?it/s]\n 20%|██        | 2/10 [00:00<00:00,  8.88it/s]\n 30%|███       | 3/10 [00:00<00:00,  7.63it/s]\n 40%|████      | 4/10 [00:00<00:00,  7.13it/s]\n 50%|█████     | 5/10 [00:00<00:00,  6.87it/s]\n 60%|██████    | 6/10 [00:00<00:00,  6.72it/s]\n 70%|███████   | 7/10 [00:01<00:00,  6.59it/s]\n 80%|████████  | 8/10 [00:01<00:00,  6.53it/s]\n 90%|█████████ | 9/10 [00:01<00:00,  6.49it/s]\n100%|██████████| 10/10 [00:01<00:00,  6.47it/s]\n100%|██████████| 10/10 [00:01<00:00,  6.78it/s]\nRequested to load AutoencoderKL\nLoading 1 new model\nExecuting node 8, title: VAE Decode, class type: VAEDecode\nExecuting node 9, title: Save Image, class type: SaveImage\nPrompt executed in 4.16 seconds\noutputs:  {'9': {'images': [{'filename': 'ComfyUI_00001_.png', 'subfolder': '', 'type': 'output'}]}}\n====================================\nContents of /tmp/outputs:\nComfyUI_00001_.png",
  "metrics": {
    "predict_time": 12.400336,
    "total_time": 12.43014
  },
  "output": [
    "https://replicate.delivery/pbxt/HV02s0HiY9JfJCwavsHeeeypu1rphkf56lpi2HqvVtftjO6rE/ComfyUI_00001_.webp"
  ],
  "started_at": "2024-04-30T11:56:50.150804Z",
  "status": "succeeded",
  "urls": {
    "get": "https://api.replicate.com/v1/predictions/5enrvraw95rgm0cf5veva7rggm",
    "cancel": "https://api.replicate.com/v1/predictions/5enrvraw95rgm0cf5veva7rggm/cancel"
  },
  "version": "a004c3ac8f62ac95a90b5a0c264beb47b66a6d1f8141b76fb27cd90e9a8bfe8e"
}

Generated in

12.4 seconds

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