Instructions to use eagle13gy/path_to_lora_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use eagle13gy/path_to_lora_model with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("CompVis/stable-diffusion-v1-4", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("eagle13gy/path_to_lora_model") prompt = "a photo of sks dog" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
Download checkpoint-100/pytorch_lora_weights.bin from eagle13gy/path_to_lora_model: direct link, hf CLI and curl.
- Browser
- Download file 3.29 MB
-
https://huggingface.co/eagle13gy/path_to_lora_model/resolve/main/checkpoint-100/pytorch_lora_weights.bin
- Command line
-
hf download hf://eagle13gy/path_to_lora_model/checkpoint-100/pytorch_lora_weights.bin
-
curl -L -o pytorch_lora_weights.bin https://huggingface.co/eagle13gy/path_to_lora_model/resolve/main/checkpoint-100/pytorch_lora_weights.bin
3.29 MB
- Xet hash:
- 970aa29e6914e2305e30758145b36447fa6f9904b6deebb2d4397f24a329291e
- Size of remote file:
- 3.29 MB
- SHA256:
- 77674be54d20310760fea8497f9073f8a7f81e9f06877ab6e738d5841a38d2b5
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