Instructions to use Atomik31/JLNLORA with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Atomik31/JLNLORA 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("Atomik31/JLNLORA") prompt = "JLN" image = pipe(prompt).images[0] - Inference
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
Add JLNLORA.safetensors
Browse files- JLNLORA.safetensors +3 -0
JLNLORA.safetensors
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version https://git-lfs.github.com/spec/v1
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oid sha256:9222f614dcd42665ef43b05c32c1480b3e5f576c29e62094ad3d7937696bccca
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size 171969336
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