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README.md
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- en
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tags:
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- flux
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base_model: "black-forest-labs/FLUX.1-dev"
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pipeline_tag: text-to-image
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---
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Trained on Replicate using:
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https://replicate.com/ostris/flux-dev-lora-trainer/train
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- en
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tags:
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- flux
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- diffusers
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- lora
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- replicate
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base_model: "black-forest-labs/FLUX.1-dev"
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pipeline_tag: text-to-image
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# widget:
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# - text: >-
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# prompt
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# output:
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# url: https://...
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instance_prompt: "2004"
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---
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# Flux 2004
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<Gallery />
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Run on Replicate:
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https://replicate.com/fofr/flux-2004
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Trained on Replicate using:
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https://replicate.com/ostris/flux-dev-lora-trainer/train
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## Trigger words
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You should use `2004` to trigger the image generation.
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## Use it with the [🧨 diffusers library](https://github.com/huggingface/diffusers)
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```py
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from diffusers import AutoPipelineForText2Image
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import torch
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pipeline = AutoPipelineForText2Image.from_pretrained('black-forest-labs/FLUX.1-dev', torch_dtype=torch.float16).to('cuda')
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pipeline.load_lora_weights('fofr/flux-2004', weight_name='lora.safetensors')
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image = pipeline('your prompt').images[0]
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```
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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)
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