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
- Prompt
- screenprint tshirt design, a happy cat holding a sign that says "I LOVE REPLICATE", ATMGRN illustration style, green
- Prompt
- a woman, ATMGRN illustration style
- Prompt
- incredibly intricate and detailed illustrated abstract art iphone wallpaper, ATMGRN illustration style, green
- Prompt
- a fall landscape, ATMGRN illustration style
- Prompt
- A punk rock frog in a studded leather jacket shouting into a microphone while standing on a stump, ATMGRN illustration style, blue tint
- Prompt
- a penguin that is a car, ATMGRN illustration style, blue tint"
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.
{
"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
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