Instructions to use eugenebokhan/saved_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use eugenebokhan/saved_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("runwayml/stable-diffusion-v1-5", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("eugenebokhan/saved_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/optimizer.bin from eugenebokhan/saved_model: direct link, hf CLI and curl.
- Browser
- Download file 9.03 MB
-
https://huggingface.co/eugenebokhan/saved_model/resolve/main/checkpoint-100/optimizer.bin
- Command line
-
hf download hf://eugenebokhan/saved_model/checkpoint-100/optimizer.bin
-
curl -L -o optimizer.bin https://huggingface.co/eugenebokhan/saved_model/resolve/main/checkpoint-100/optimizer.bin
9.03 MB
- Xet hash:
- c0e6b364cd59b51f9f37cc1bd8a44058b8e9bd274b32ee283c37db95ffda2352
- Size of remote file:
- 9.03 MB
- SHA256:
- da94ccc01c0a9920fb4de1ec91e7d6e918ac5fa2b08283aaf83e699a0a2e1c53
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