Instructions to use SidXXD/coarse_5-initialize_specific with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use SidXXD/coarse_5-initialize_specific with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("SidXXD/coarse_5-initialize_specific", dtype=torch.bfloat16, device_map="cuda") prompt = "None" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
Download checkpoint-500/optimizer.bin from SidXXD/coarse_5-initialize_specific: direct link, hf CLI and curl.
- Browser
- Download file 457 MB
-
https://huggingface.co/SidXXD/coarse_5-initialize_specific/resolve/main/checkpoint-500/optimizer.bin
- Command line
-
hf download hf://SidXXD/coarse_5-initialize_specific/checkpoint-500/optimizer.bin
-
curl -L -o optimizer.bin https://huggingface.co/SidXXD/coarse_5-initialize_specific/resolve/main/checkpoint-500/optimizer.bin
457 MB
- Xet hash:
- dce321b1fba98cb10fef62a851bba7336811b0b0f158e40245cc0e7128c7fe24
- Size of remote file:
- 457 MB
- SHA256:
- 1c381e69c0fd087da29be6abded0044e0dd73a77db30cde57626c7ca0d26223c
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.