---
license: other
license_name: flux-1-dev-non-commercial-license
license_link: https://huggingface.co/black-forest-labs/FLUX.1-dev/blob/main/LICENSE.md
language:
  - en
tags:
  - flux
  - diffusers
  - lora
  - replicate
base_model: "black-forest-labs/FLUX.1-dev"
pipeline_tag: text-to-image
widget:
  - text: 'screenprint tshirt design, a happy cat holding a sign that says "I LOVE REPLICATE", ATMGRN illustration style, green'
    output:
      url: "images/1.webp"

  - text: "a woman, ATMGRN illustration style"
    output:
      url: "images/2.webp"

  - text: "incredibly intricate and detailed illustrated abstract art iphone wallpaper, ATMGRN illustration style, green"
    output:
      url: "images/3.webp"

  - text: "a fall landscape, ATMGRN illustration style"
    output:
      url: "images/4.webp"

  - text: "A punk rock frog in a studded leather jacket shouting into a microphone while standing on a stump, ATMGRN illustration style, blue tint"
    output:
      url: "images/5.webp"

  - text: a penguin that is a car, ATMGRN illustration style, blue tint"
    output:
      url: "images/6.webp"

instance_prompt: ATMGRN
---

# Flux Autumn Green

<Gallery />

Trained on Replicate using:

https://replicate.com/ostris/flux-dev-lora-trainer/train

## Trigger words

You should use `ATMGRN` to trigger the image generation.

## Training details

This model was trained on Replicate, here: https://replicate.com/ostris/flux-dev-lora-trainer/train

The training set is comprised of 14 images generated on MidJourney using the --sref 2795713976.

You can find the entire training set, including auto-generated captions, and training images in the `./training_set` directory.

Below are the training parameters I used, which seem to work fairly well for illustration/cartoony Flux LoRAs.

NOTE: This is 3200 training steps in total. The reason the `steps` parameter is `800`, is because I did a `batch_size` of `4`.

```json
{
  "steps": 800,
  "lora_rank": 24,
  "batch_size": 4,
  "autocaption": true,
  "input_images": "training_set/2024-09-23-autumn-green.zip",
  "trigger_word": "ATMGRN",
  "learning_rate": 0.0003,
  "autocaption_suffix": "ATMGRN style"
}
```

## Use it with the [🧨 diffusers library](https://github.com/huggingface/diffusers)

```py
from diffusers import AutoPipelineForText2Image
import torch

pipeline = AutoPipelineForText2Image.from_pretrained('black-forest-labs/FLUX.1-dev', torch_dtype=torch.float16).to('cuda')
pipeline.load_lora_weights('jakedahn/flux-autumn-green', weight_name='lora.safetensors')
image = pipeline('cat with a hat, ATMGRN illustration style').images[0]
```

For more details, including weighting, merging and fusing LoRAs, check the [documentation on loading LoRAs in diffusers](https://huggingface.co/docs/diffusers/main/en/using-diffusers/loading_adapters)