flux-lora-blobfish / README.md
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Add generated example (#3)
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---
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
base_model: black-forest-labs/FLUX.1-schnell
pipeline_tag: text-to-image
instance_prompt: BLBFSH
library_name: diffusers
inference:
parameters:
width: 1024
height: 1024
widget:
- text: A cartoon of BLBFSH
output:
url: images/example_f7z6qh2ud.png
- text: >-
a BLBFSH fish swimming in the ocean. 3D pixar style cartoon movie. Side
camera.
output:
url: images/example_h7gruf2n6.png
- text: >-
a light pink BLBFSH fish swimming in the ocean. 3D pixar style cartoon
movie. Side camera.
output:
url: images/example_lzi5mu3hp.png
---
# Flux Dott Remastered
Trained on Replicate using:
https://replicate.com/ostris/flux-dev-lora-trainer/train
## Trigger words
You should use `BLBFSH` to trigger the image generation.
<Gallery />
## 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('lichorosario/flux-dott-remastered', weight_name='lora.safetensors')
image = pipeline('your prompt').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)