Instructions to use brunnolou/bruno-lora with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use brunnolou/bruno-lora with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("black-forest-labs/FLUX.1-dev", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("brunnolou/bruno-lora") prompt = "TOK" image = pipe(prompt).images[0] - Inference
- Notebooks
- Google Colab
- Kaggle
- Local Apps
- Draw Things
- DiffusionBee
Upload folder using huggingface_hub
Browse files- config.yaml +2 -2
- lora.safetensors +3 -0
config.yaml
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job:
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config:
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name: flux_train_replicate
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process:
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- type:
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training_folder: output
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device: cuda:0
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trigger_word: TOK
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job: custom_job
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config:
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name: flux_train_replicate
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process:
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- type: custom_sd_trainer
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training_folder: output
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device: cuda:0
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trigger_word: TOK
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lora.safetensors
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version https://git-lfs.github.com/spec/v1
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oid sha256:3f1ab64826b677faf8e07cf8492580d59ee5cd84a0e9cd6f978f23741fae729f
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size 171969408
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