Prediction

Model

jensbosseparra/flux1-schnell-multi-lora:1af36f42

f7rqmrn7q9rj00cjyc9sf4f0wr

Status

Succeeded

Source

Web

Hardware

A100 (80GB)

Total duration

6.3s

Created

about 1 year ago

Webhook

–

Input

prompt: a beautiful scandinavian girl posing in the mountains, the sun is shining, the grass is green and flowers are everywhere, she is wearing a patterned colorful top. be4u7y
aspect_ratio: 1:1
prompt_strength: 0.8
num_outputs: 1
num_inference_steps: 4
guidance_scale: 0
seed: 43
output_format: webp
output_quality: 100
hf_loras: https://huggingface.co/Octree/flux-schnell-lora/resolve/main/flux-schnell-lora.safetensors, https://huggingface.co/hugovntr/flux-schnell-realism/resolve/main/schnell-realism_v1.safetensors
lora_scales

{
  "aspect_ratio": "1:1",
  "guidance_scale": 0,
  "hf_loras": [
    "https://huggingface.co/Octree/flux-schnell-lora/resolve/main/flux-schnell-lora.safetensors",
    "https://huggingface.co/hugovntr/flux-schnell-realism/resolve/main/schnell-realism_v1.safetensors"
  ],
  "lora_scales": [
    0.8,
    0.9
  ],
  "num_inference_steps": 4,
  "num_outputs": 1,
  "output_format": "webp",
  "output_quality": 100,
  "prompt": "a beautiful scandinavian girl posing in the mountains, the sun is shining, the grass is green and flowers are everywhere, she is wearing a patterned colorful top. be4u7y",
  "prompt_strength": 0.8,
  "seed": 43
}

Install Replicate’s Node.js client library:

npm install replicate

Set the REPLICATE_API_TOKEN environment variable:

export REPLICATE_API_TOKEN=r8_TQU**********************************

This is your API token. Keep it to yourself.

Import and set up the client:

import Replicate from "replicate";
import fs from "node:fs";

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

Run jensbosseparra/flux1-schnell-multi-lora using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

const output = await replicate.run(
  "jensbosseparra/flux1-schnell-multi-lora:1af36f429c0be8b88f7f8adfe6e720d9f1ab3b72ab62c78e768d08e91e4c7b68",
  {
    input: {
      aspect_ratio: "1:1",
      guidance_scale: 0,
      hf_loras: ["https://huggingface.co/Octree/flux-schnell-lora/resolve/main/flux-schnell-lora.safetensors","https://huggingface.co/hugovntr/flux-schnell-realism/resolve/main/schnell-realism_v1.safetensors"],
      lora_scales: [0.8,0.9],
      num_inference_steps: 4,
      num_outputs: 1,
      output_format: "webp",
      output_quality: 100,
      prompt: "a beautiful scandinavian girl posing in the mountains, the sun is shining, the grass is green and flowers are everywhere, she is wearing a patterned colorful top. be4u7y",
      prompt_strength: 0.8,
      seed: 43
    }
  }
);

// To access the file URL:
console.log(output[0].url()); //=> "http://example.com"

// To write the file to disk:
fs.writeFile("my-image.png", output[0]);

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=r8_TQU**********************************

This is your API token. Keep it to yourself.

Import the client:

import replicate

Run jensbosseparra/flux1-schnell-multi-lora using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

output = replicate.run(
    "jensbosseparra/flux1-schnell-multi-lora:1af36f429c0be8b88f7f8adfe6e720d9f1ab3b72ab62c78e768d08e91e4c7b68",
    input={
        "aspect_ratio": "1:1",
        "guidance_scale": 0,
        "hf_loras": ["https://huggingface.co/Octree/flux-schnell-lora/resolve/main/flux-schnell-lora.safetensors","https://huggingface.co/hugovntr/flux-schnell-realism/resolve/main/schnell-realism_v1.safetensors"],
        "lora_scales": [0.8,0.9],
        "num_inference_steps": 4,
        "num_outputs": 1,
        "output_format": "webp",
        "output_quality": 100,
        "prompt": "a beautiful scandinavian girl posing in the mountains, the sun is shining, the grass is green and flowers are everywhere, she is wearing a patterned colorful top. be4u7y",
        "prompt_strength": 0.8,
        "seed": 43
    }
)

# To access the file URL:
print(output[0].url())
#=> "http://example.com"

# To write the file to disk:
with open("my-image.png", "wb") as file:
    file.write(output[0].read())

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=r8_TQU**********************************

This is your API token. Keep it to yourself.

Run jensbosseparra/flux1-schnell-multi-lora 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": "jensbosseparra/flux1-schnell-multi-lora:1af36f429c0be8b88f7f8adfe6e720d9f1ab3b72ab62c78e768d08e91e4c7b68",
    "input": {
      "aspect_ratio": "1:1",
      "guidance_scale": 0,
      "hf_loras": ["https://huggingface.co/Octree/flux-schnell-lora/resolve/main/flux-schnell-lora.safetensors","https://huggingface.co/hugovntr/flux-schnell-realism/resolve/main/schnell-realism_v1.safetensors"],
      "lora_scales": [0.8,0.9],
      "num_inference_steps": 4,
      "num_outputs": 1,
      "output_format": "webp",
      "output_quality": 100,
      "prompt": "a beautiful scandinavian girl posing in the mountains, the sun is shining, the grass is green and flowers are everywhere, she is wearing a patterned colorful top. be4u7y",
      "prompt_strength": 0.8,
      "seed": 43
    }
  }' \
  https://api.replicate.com/v1/predictions

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

Output

{
  "id": "f7rqmrn7q9rj00cjyc9sf4f0wr",
  "model": "jensbosseparra/flux1-schnell-multi-lora",
  "version": "1af36f429c0be8b88f7f8adfe6e720d9f1ab3b72ab62c78e768d08e91e4c7b68",
  "input": {
    "aspect_ratio": "1:1",
    "guidance_scale": 0,
    "hf_loras": [
      "https://huggingface.co/Octree/flux-schnell-lora/resolve/main/flux-schnell-lora.safetensors",
      "https://huggingface.co/hugovntr/flux-schnell-realism/resolve/main/schnell-realism_v1.safetensors"
    ],
    "lora_scales": [
      0.8,
      0.9
    ],
    "num_inference_steps": 4,
    "num_outputs": 1,
    "output_format": "webp",
    "output_quality": 100,
    "prompt": "a beautiful scandinavian girl posing in the mountains, the sun is shining, the grass is green and flowers are everywhere, she is wearing a patterned colorful top. be4u7y",
    "prompt_strength": 0.8,
    "seed": 43
  },
  "logs": "Using seed: 43\nPrompt: a beautiful scandinavian girl posing in the mountains, the sun is shining, the grass is green and flowers are everywhere, she is wearing a patterned colorful top. be4u7y\ntxt2img mode\nDownloading LoRA weights from - HF URL: https://huggingface.co/Octree/flux-schnell-lora/resolve/main/flux-schnell-lora.safetensors\nHuggingFace slug from URL: Octree/flux-schnell-lora, weight name: flux-schnell-lora.safetensors\nLoading LoRA took: 0.68 seconds\nDownloading LoRA weights from - HF URL: https://huggingface.co/hugovntr/flux-schnell-realism/resolve/main/schnell-realism_v1.safetensors\nHuggingFace slug from URL: hugovntr/flux-schnell-realism, weight name: schnell-realism_v1.safetensors\nUnsuppored keys for ai-toolkit: dict_keys(['lora_te1_text_model_encoder_layers_0_mlp_fc1.alpha', 'lora_te1_text_model_encoder_layers_0_mlp_fc1.lora_down.weight', 'lora_te1_text_model_encoder_layers_0_mlp_fc1.lora_up.weight', 'lora_te1_text_model_encoder_layers_0_mlp_fc2.alpha', 'lora_te1_text_model_encoder_layers_0_mlp_fc2.lora_down.weight', 'lora_te1_text_model_encoder_layers_0_mlp_fc2.lora_up.weight', 'lora_te1_text_model_encoder_layers_0_self_attn_k_proj.alpha', 'lora_te1_text_model_encoder_layers_0_self_attn_k_proj.lora_down.weight', 'lora_te1_text_model_encoder_layers_0_self_attn_k_proj.lora_up.weight', 'lora_te1_text_model_encoder_layers_0_self_attn_out_proj.alpha', 'lora_te1_text_model_encoder_layers_0_self_attn_out_proj.lora_down.weight', 'lora_te1_text_model_encoder_layers_0_self_attn_out_proj.lora_up.weight', 'lora_te1_text_model_encoder_layers_0_self_attn_q_proj.alpha', 'lora_te1_text_model_encoder_layers_0_self_attn_q_proj.lora_down.weight', 'lora_te1_text_model_encoder_layers_0_self_attn_q_proj.lora_up.weight', 'lora_te1_text_model_encoder_layers_0_self_attn_v_proj.alpha', 'lora_te1_text_model_encoder_layers_0_self_attn_v_proj.lora_down.weight', 'lora_te1_text_model_encoder_layers_0_self_attn_v_proj.lora_up.weight', 'lora_te1_text_model_encoder_layers_10_mlp_fc1.alpha', 'lora_te1_text_model_encoder_layers_10_mlp_fc1.lora_down.weight', 'lora_te1_text_model_encoder_layers_10_mlp_fc1.lora_up.weight', 'lora_te1_text_model_encoder_layers_10_mlp_fc2.alpha', 'lora_te1_text_model_encoder_layers_10_mlp_fc2.lora_down.weight', 'lora_te1_text_model_encoder_layers_10_mlp_fc2.lora_up.weight', 'lora_te1_text_model_encoder_layers_10_self_attn_k_proj.alpha', 'lora_te1_text_model_encoder_layers_10_self_attn_k_proj.lora_down.weight', 'lora_te1_text_model_encoder_layers_10_self_attn_k_proj.lora_up.weight', 'lora_te1_text_model_encoder_layers_10_self_attn_out_proj.alpha', 'lora_te1_text_model_encoder_layers_10_self_attn_out_proj.lora_down.weight', 'lora_te1_text_model_encoder_layers_10_self_attn_out_proj.lora_up.weight', 'lora_te1_text_model_encoder_layers_10_self_attn_q_proj.alpha', 'lora_te1_text_model_encoder_layers_10_self_attn_q_proj.lora_down.weight', 'lora_te1_text_model_encoder_layers_10_self_attn_q_proj.lora_up.weight', 'lora_te1_text_model_encoder_layers_10_self_attn_v_proj.alpha', 'lora_te1_text_model_encoder_layers_10_self_attn_v_proj.lora_down.weight', 'lora_te1_text_model_encoder_layers_10_self_attn_v_proj.lora_up.weight', 'lora_te1_text_model_encoder_layers_11_mlp_fc1.alpha', 'lora_te1_text_model_encoder_layers_11_mlp_fc1.lora_down.weight', 'lora_te1_text_model_encoder_layers_11_mlp_fc1.lora_up.weight', 'lora_te1_text_model_encoder_layers_11_mlp_fc2.alpha', 'lora_te1_text_model_encoder_layers_11_mlp_fc2.lora_down.weight', 'lora_te1_text_model_encoder_layers_11_mlp_fc2.lora_up.weight', 'lora_te1_text_model_encoder_layers_11_self_attn_k_proj.alpha', 'lora_te1_text_model_encoder_layers_11_self_attn_k_proj.lora_down.weight', 'lora_te1_text_model_encoder_layers_11_self_attn_k_proj.lora_up.weight', 'lora_te1_text_model_encoder_layers_11_self_attn_out_proj.alpha', 'lora_te1_text_model_encoder_layers_11_self_attn_out_proj.lora_down.weight', 'lora_te1_text_model_encoder_layers_11_self_attn_out_proj.lora_up.weight', 'lora_te1_text_model_encoder_layers_11_self_attn_q_proj.alpha', 'lora_te1_text_model_encoder_layers_11_self_attn_q_proj.lora_down.weight', 'lora_te1_text_model_encoder_layers_11_self_attn_q_proj.lora_up.weight', 'lora_te1_text_model_encoder_layers_11_self_attn_v_proj.alpha', 'lora_te1_text_model_encoder_layers_11_self_attn_v_proj.lora_down.weight', 'lora_te1_text_model_encoder_layers_11_self_attn_v_proj.lora_up.weight', 'lora_te1_text_model_encoder_layers_1_mlp_fc1.alpha', 'lora_te1_text_model_encoder_layers_1_mlp_fc1.lora_down.weight', 'lora_te1_text_model_encoder_layers_1_mlp_fc1.lora_up.weight', 'lora_te1_text_model_encoder_layers_1_mlp_fc2.alpha', 'lora_te1_text_model_encoder_layers_1_mlp_fc2.lora_down.weight', 'lora_te1_text_model_encoder_layers_1_mlp_fc2.lora_up.weight', 'lora_te1_text_model_encoder_layers_1_self_attn_k_proj.alpha', 'lora_te1_text_model_encoder_layers_1_self_attn_k_proj.lora_down.weight', 'lora_te1_text_model_encoder_layers_1_self_attn_k_proj.lora_up.weight', 'lora_te1_text_model_encoder_layers_1_self_attn_out_proj.alpha', 'lora_te1_text_model_encoder_layers_1_self_attn_out_proj.lora_down.weight', 'lora_te1_text_model_encoder_layers_1_self_attn_out_proj.lora_up.weight', 'lora_te1_text_model_encoder_layers_1_self_attn_q_proj.alpha', 'lora_te1_text_model_encoder_layers_1_self_attn_q_proj.lora_down.weight', 'lora_te1_text_model_encoder_layers_1_self_attn_q_proj.lora_up.weight', 'lora_te1_text_model_encoder_layers_1_self_attn_v_proj.alpha', 'lora_te1_text_model_encoder_layers_1_self_attn_v_proj.lora_down.weight', 'lora_te1_text_model_encoder_layers_1_self_attn_v_proj.lora_up.weight', 'lora_te1_text_model_encoder_layers_2_mlp_fc1.alpha', 'lora_te1_text_model_encoder_layers_2_mlp_fc1.lora_down.weight', 'lora_te1_text_model_encoder_layers_2_mlp_fc1.lora_up.weight', 'lora_te1_text_model_encoder_layers_2_mlp_fc2.alpha', 'lora_te1_text_model_encoder_layers_2_mlp_fc2.lora_down.weight', 'lora_te1_text_model_encoder_layers_2_mlp_fc2.lora_up.weight', 'lora_te1_text_model_encoder_layers_2_self_attn_k_proj.alpha', 'lora_te1_text_model_encoder_layers_2_self_attn_k_proj.lora_down.weight', 'lora_te1_text_model_encoder_layers_2_self_attn_k_proj.lora_up.weight', 'lora_te1_text_model_encoder_layers_2_self_attn_out_proj.alpha', 'lora_te1_text_model_encoder_layers_2_self_attn_out_proj.lora_down.weight', 'lora_te1_text_model_encoder_layers_2_self_attn_out_proj.lora_up.weight', 'lora_te1_text_model_encoder_layers_2_self_attn_q_proj.alpha', 'lora_te1_text_model_encoder_layers_2_self_attn_q_proj.lora_down.weight', 'lora_te1_text_model_encoder_layers_2_self_attn_q_proj.lora_up.weight', 'lora_te1_text_model_encoder_layers_2_self_attn_v_proj.alpha', 'lora_te1_text_model_encoder_layers_2_self_attn_v_proj.lora_down.weight', 'lora_te1_text_model_encoder_layers_2_self_attn_v_proj.lora_up.weight', 'lora_te1_text_model_encoder_layers_3_mlp_fc1.alpha', 'lora_te1_text_model_encoder_layers_3_mlp_fc1.lora_down.weight', 'lora_te1_text_model_encoder_layers_3_mlp_fc1.lora_up.weight', 'lora_te1_text_model_encoder_layers_3_mlp_fc2.alpha', 'lora_te1_text_model_encoder_layers_3_mlp_fc2.lora_down.weight', 'lora_te1_text_model_encoder_layers_3_mlp_fc2.lora_up.weight', 'lora_te1_text_model_encoder_layers_3_self_attn_k_proj.alpha', 'lora_te1_text_model_encoder_layers_3_self_attn_k_proj.lora_down.weight', 'lora_te1_text_model_encoder_layers_3_self_attn_k_proj.lora_up.weight', 'lora_te1_text_model_encoder_layers_3_self_attn_out_proj.alpha', 'lora_te1_text_model_encoder_layers_3_self_attn_out_proj.lora_down.weight', 'lora_te1_text_model_encoder_layers_3_self_attn_out_proj.lora_up.weight', 'lora_te1_text_model_encoder_layers_3_self_attn_q_proj.alpha', 'lora_te1_text_model_encoder_layers_3_self_attn_q_proj.lora_down.weight', 'lora_te1_text_model_encoder_layers_3_self_attn_q_proj.lora_up.weight', 'lora_te1_text_model_encoder_layers_3_self_attn_v_proj.alpha', 'lora_te1_text_model_encoder_layers_3_self_attn_v_proj.lora_down.weight', 'lora_te1_text_model_encoder_layers_3_self_attn_v_proj.lora_up.weight', 'lora_te1_text_model_encoder_layers_4_mlp_fc1.alpha', 'lora_te1_text_model_encoder_layers_4_mlp_fc1.lora_down.weight', 'lora_te1_text_model_encoder_layers_4_mlp_fc1.lora_up.weight', 'lora_te1_text_model_encoder_layers_4_mlp_fc2.alpha', 'lora_te1_text_model_encoder_layers_4_mlp_fc2.lora_down.weight', 'lora_te1_text_model_encoder_layers_4_mlp_fc2.lora_up.weight', 'lora_te1_text_model_encoder_layers_4_self_attn_k_proj.alpha', 'lora_te1_text_model_encoder_layers_4_self_attn_k_proj.lora_down.weight', 'lora_te1_text_model_encoder_layers_4_self_attn_k_proj.lora_up.weight', 'lora_te1_text_model_encoder_layers_4_self_attn_out_proj.alpha', 'lora_te1_text_model_encoder_layers_4_self_attn_out_proj.lora_down.weight', 'lora_te1_text_model_encoder_layers_4_self_attn_out_proj.lora_up.weight', 'lora_te1_text_model_encoder_layers_4_self_attn_q_proj.alpha', 'lora_te1_text_model_encoder_layers_4_self_attn_q_proj.lora_down.weight', 'lora_te1_text_model_encoder_layers_4_self_attn_q_proj.lora_up.weight', 'lora_te1_text_model_encoder_layers_4_self_attn_v_proj.alpha', 'lora_te1_text_model_encoder_layers_4_self_attn_v_proj.lora_down.weight', 'lora_te1_text_model_encoder_layers_4_self_attn_v_proj.lora_up.weight', 'lora_te1_text_model_encoder_layers_5_mlp_fc1.alpha', 'lora_te1_text_model_encoder_layers_5_mlp_fc1.lora_down.weight', 'lora_te1_text_model_encoder_layers_5_mlp_fc1.lora_up.weight', 'lora_te1_text_model_encoder_layers_5_mlp_fc2.alpha', 'lora_te1_text_model_encoder_layers_5_mlp_fc2.lora_down.weight', 'lora_te1_text_model_encoder_layers_5_mlp_fc2.lora_up.weight', 'lora_te1_text_model_encoder_layers_5_self_attn_k_proj.alpha', 'lora_te1_text_model_encoder_layers_5_self_attn_k_proj.lora_down.weight', 'lora_te1_text_model_encoder_layers_5_self_attn_k_proj.lora_up.weight', 'lora_te1_text_model_encoder_layers_5_self_attn_out_proj.alpha', 'lora_te1_text_model_encoder_layers_5_self_attn_out_proj.lora_down.weight', 'lora_te1_text_model_encoder_layers_5_self_attn_out_proj.lora_up.weight', 'lora_te1_text_model_encoder_layers_5_self_attn_q_proj.alpha', 'lora_te1_text_model_encoder_layers_5_self_attn_q_proj.lora_down.weight', 'lora_te1_text_model_encoder_layers_5_self_attn_q_proj.lora_up.weight', 'lora_te1_text_model_encoder_layers_5_self_attn_v_proj.alpha', 'lora_te1_text_model_encoder_layers_5_self_attn_v_proj.lora_down.weight', 'lora_te1_text_model_encoder_layers_5_self_attn_v_proj.lora_up.weight', 'lora_te1_text_model_encoder_layers_6_mlp_fc1.alpha', 'lora_te1_text_model_encoder_layers_6_mlp_fc1.lora_down.weight', 'lora_te1_text_model_encoder_layers_6_mlp_fc1.lora_up.weight', 'lora_te1_text_model_encoder_layers_6_mlp_fc2.alpha', 'lora_te1_text_model_encoder_layers_6_mlp_fc2.lora_down.weight', 'lora_te1_text_model_encoder_layers_6_mlp_fc2.lora_up.weight', 'lora_te1_text_model_encoder_layers_6_self_attn_k_proj.alpha', 'lora_te1_text_model_encoder_layers_6_self_attn_k_proj.lora_down.weight', 'lora_te1_text_model_encoder_layers_6_self_attn_k_proj.lora_up.weight', 'lora_te1_text_model_encoder_layers_6_self_attn_out_proj.alpha', 'lora_te1_text_model_encoder_layers_6_self_attn_out_proj.lora_down.weight', 'lora_te1_text_model_encoder_layers_6_self_attn_out_proj.lora_up.weight', 'lora_te1_text_model_encoder_layers_6_self_attn_q_proj.alpha', 'lora_te1_text_model_encoder_layers_6_self_attn_q_proj.lora_down.weight', 'lora_te1_text_model_encoder_layers_6_self_attn_q_proj.lora_up.weight', 'lora_te1_text_model_encoder_layers_6_self_attn_v_proj.alpha', 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2.26it/s]\n100%|██████████| 4/4 [00:01<00:00,  2.18it/s]\n100%|██████████| 4/4 [00:01<00:00,  2.19it/s]",
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  "created_at": "2024-11-03T17:30:04.602Z",
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Generated in

6.3 seconds

Tweak it Report

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