Instructions to use chentxxx/Lora with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use chentxxx/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("runwayml/stable-diffusion-v1-5", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("chentxxx/Lora") prompt = "a photo of jiaran girl" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
Download checkpoint-100/pytorch_model.bin from chentxxx/Lora: direct link, hf CLI and curl.
- Browser
- Download file 3.28 MB
-
https://huggingface.co/chentxxx/Lora/resolve/main/checkpoint-100/pytorch_model.bin
- Command line
-
hf download hf://chentxxx/Lora/checkpoint-100/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/chentxxx/Lora/resolve/main/checkpoint-100/pytorch_model.bin
3.28 MB
- Xet hash:
- b8349946d353b07df881306b97903fe3c74b27a4556556101de45c09b0cbf2a6
- Size of remote file:
- 3.28 MB
- SHA256:
- 070f0e659e45ca98dabbcda678cd09ce6132094600dacc212058bfa6ca5921ea
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