Instructions to use Boqiang/path-to-save-model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Boqiang/path-to-save-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("Boqiang/path-to-save-model") prompt = "a photo of sks dog" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
Download checkpoint-200/optimizer.bin from Boqiang/path-to-save-model: direct link, hf CLI and curl.
- Browser
- Download file 6.59 MB
-
https://huggingface.co/Boqiang/path-to-save-model/resolve/main/checkpoint-200/optimizer.bin
- Command line
-
hf download hf://Boqiang/path-to-save-model/checkpoint-200/optimizer.bin
-
curl -L -o optimizer.bin https://huggingface.co/Boqiang/path-to-save-model/resolve/main/checkpoint-200/optimizer.bin
6.59 MB
- Xet hash:
- bfa0d0578e93e5c71c0d0e94c40a45e1d175921906efe90a7622658bb9246473
- Size of remote file:
- 6.59 MB
- SHA256:
- f80660943b894453e830e7df9cf8dadb012bab90bd73e719b5baf9e089f05b47
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.