jensbosseparra/flux1-schnell-multi-lora | Run with an API on Replicate

jensbosseparra / flux1-schnell-multi-lora

Adapted to have multi-lora support also for schnell: https://replicate.com/lucataco/flux-dev-multi-lora

Cold

Public
2.5K runs
A100 (80GB)

Iterate in playground

Run with an API

Playground API Examples README Versions

Input

prompt

*string

Shift + Return to add a new line

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. be4u7ya 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 for generated image

aspect_ratio

string

Aspect ratio & resolution for the generated image. The only low res option is 512:512.

Default: "512:512"

image

file

Input image for image to image mode. The aspect ratio of your output will match this image

prompt_strength

number

(minimum: 0, maximum: 1)

Prompt strength (or denoising strength) when using image to image. 1.0 corresponds to full destruction of information in image.

Default: 0.8

num_outputs

integer

(minimum: 1, maximum: 4)

Number of images to output.

Default: 1

num_inference_steps

integer

(minimum: 1, maximum: 4)

Number of inference steps

Default: 4

guidance_scale

number

(minimum: 0, maximum: 0)

Guidance scale for the diffusion process

Default: 0

seed

integer

Random seed. Set for reproducible generation

output_format

string

Format of the output images

Default: "webp"

output_quality

integer

(minimum: 0, maximum: 100)

Quality when saving the output images, from 0 to 100. 100 is best quality, 0 is lowest quality. Not relevant for .png outputs

Default: 100

hf_loras

string[]

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

Huggingface path, or URL to the LoRA weights. Ex: alvdansen/frosting_lane_flux

lora_scales

number[]

Enter a string of numbers separated by commas

Scale for the LoRA weights. Default value is 0.8

disable_safety_checker

boolean

Disable safety checker for generated images. This feature is only available through the API. See [https://replicate.com/docs/how-does-replicate-work#safety](https://replicate.com/docs/how-does-replicate-work#safety)

Default: false

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

npx create-replicate --model=jensbosseparra/flux1-schnell-multi-lora

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";
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:85e4655b8b7d00ee7b66e2ff6986a489f710ff799bb4a62a7d7b34e66a3bdcd2",
  {
    input: {
      seed: 43,
      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",
      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_outputs: 1,
      aspect_ratio: "1:1",
      output_format: "webp",
      guidance_scale: 0,
      output_quality: 100,
      prompt_strength: 0.8,
      num_inference_steps: 4
    }
  }
);

// 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=<paste-your-token-here>

Find your API token in your account settings.

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:85e4655b8b7d00ee7b66e2ff6986a489f710ff799bb4a62a7d7b34e66a3bdcd2",
    input={
        "seed": 43,
        "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",
        "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_outputs": 1,
        "aspect_ratio": "1:1",
        "output_format": "webp",
        "guidance_scale": 0,
        "output_quality": 100,
        "prompt_strength": 0.8,
        "num_inference_steps": 4
    }
)
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 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:85e4655b8b7d00ee7b66e2ff6986a489f710ff799bb4a62a7d7b34e66a3bdcd2",
    "input": {
      "seed": 43,
      "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",
      "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_outputs": 1,
      "aspect_ratio": "1:1",
      "output_format": "webp",
      "guidance_scale": 0,
      "output_quality": 100,
      "prompt_strength": 0.8,
      "num_inference_steps": 4
    }
  }' \
  https://api.replicate.com/v1/predictions

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

Output

{
  "completed_at": "2024-11-03T17:30:10.925995Z",
  "created_at": "2024-11-03T17:30:04.602000Z",
  "data_removed": false,
  "error": null,
  "id": "f7rqmrn7q9rj00cjyc9sf4f0wr",
  "input": {
    "seed": 43,
    "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",
    "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_outputs": 1,
    "aspect_ratio": "1:1",
    "output_format": "webp",
    "guidance_scale": 0,
    "output_quality": 100,
    "prompt_strength": 0.8,
    "num_inference_steps": 4
  },
  "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', 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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]",
  "metrics": {
    "predict_time": 6.315119646,
    "total_time": 6.323995
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  "output": [
    "https://replicate.delivery/yhqm/YPC4ZAAnzxamDtTFLBsOrXUsfYDfBib2bnzVNtd3KMwiUWtTA/out-0.webp"
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  "started_at": "2024-11-03T17:30:04.610875Z",
  "status": "succeeded",
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    "get": "https://api.replicate.com/v1/predictions/f7rqmrn7q9rj00cjyc9sf4f0wr",
    "cancel": "https://api.replicate.com/v1/predictions/f7rqmrn7q9rj00cjyc9sf4f0wr/cancel"
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  "version": "1af36f429c0be8b88f7f8adfe6e720d9f1ab3b72ab62c78e768d08e91e4c7b68"
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Generated in

6.3 seconds

Tweak it ShareReport View full prediction

Using seed: 43
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
txt2img mode
Downloading LoRA weights from - HF URL: https://huggingface.co/Octree/flux-schnell-lora/resolve/main/flux-schnell-lora.safetensors
HuggingFace slug from URL: Octree/flux-schnell-lora, weight name: flux-schnell-lora.safetensors
Loading LoRA took: 0.68 seconds
Downloading LoRA weights from - HF URL: https://huggingface.co/hugovntr/flux-schnell-realism/resolve/main/schnell-realism_v1.safetensors
HuggingFace slug from URL: hugovntr/flux-schnell-realism, weight name: schnell-realism_v1.safetensors
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'lora_te1_text_model_encoder_layers_9_mlp_fc2.lora_down.weight', 'lora_te1_text_model_encoder_layers_9_mlp_fc2.lora_up.weight', 'lora_te1_text_model_encoder_layers_9_self_attn_k_proj.alpha', 'lora_te1_text_model_encoder_layers_9_self_attn_k_proj.lora_down.weight', 'lora_te1_text_model_encoder_layers_9_self_attn_k_proj.lora_up.weight', 'lora_te1_text_model_encoder_layers_9_self_attn_out_proj.alpha', 'lora_te1_text_model_encoder_layers_9_self_attn_out_proj.lora_down.weight', 'lora_te1_text_model_encoder_layers_9_self_attn_out_proj.lora_up.weight', 'lora_te1_text_model_encoder_layers_9_self_attn_q_proj.alpha', 'lora_te1_text_model_encoder_layers_9_self_attn_q_proj.lora_down.weight', 'lora_te1_text_model_encoder_layers_9_self_attn_q_proj.lora_up.weight', 'lora_te1_text_model_encoder_layers_9_self_attn_v_proj.alpha', 'lora_te1_text_model_encoder_layers_9_self_attn_v_proj.lora_down.weight', 'lora_te1_text_model_encoder_layers_9_self_attn_v_proj.lora_up.weight'])
Loading LoRA took: 2.27 seconds
  0%|          | 0/4 [00:00<?, ?it/s]
 25%|██▌       | 1/4 [00:00<00:01,  1.85it/s]
 50%|█████     | 2/4 [00:00<00:00,  2.45it/s]
 75%|███████▌  | 3/4 [00:01<00:00,  2.26it/s]
100%|██████████| 4/4 [00:01<00:00,  2.18it/s]
100%|██████████| 4/4 [00:01<00:00,  2.19it/s]

This output was created using a different version of the model, jensbosseparra/flux1-schnell-multi-lora:1af36f42.

Examples

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Run time and cost

This model costs approximately $0.0018 to run on Replicate, or 555 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 2 seconds.

Readme

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