Instructions to use bulwaith/output with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use bulwaith/output with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("stable-diffusion-v1-5/stable-diffusion-v1-5", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("bulwaith/output") prompt = "a photo of sks antonio" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
Download checkpoint-400/optimizer.bin from bulwaith/output: direct link, hf CLI and curl.
- Browser
- Download file 6.58 MB
-
https://huggingface.co/bulwaith/output/resolve/main/checkpoint-400/optimizer.bin
- Command line
-
hf download hf://bulwaith/output/checkpoint-400/optimizer.bin
-
curl -L -o optimizer.bin https://huggingface.co/bulwaith/output/resolve/main/checkpoint-400/optimizer.bin
6.58 MB
- Xet hash:
- c5e55e28760fcc2986726530bf6caa216528312f43bf03f0e349b87e8bdc2429
- Size of remote file:
- 6.58 MB
- SHA256:
- d62b8ea8e7820bfcfdac856b8f5209bfabf7c5eb9c74ee61c0c15a28584e321a
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.