Instructions to use TheLitttleThings/DiffusionTest1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use TheLitttleThings/DiffusionTest1 with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import HybridCLIP model = HybridCLIP.from_pretrained("TheLitttleThings/DiffusionTest1", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download 13/flax_model.msgpack from TheLitttleThings/DiffusionTest1: direct link, hf CLI and curl.
- Browser
- Download file 852 MB
-
https://huggingface.co/TheLitttleThings/DiffusionTest1/resolve/main/13/flax_model.msgpack
- Command line
-
hf download hf://TheLitttleThings/DiffusionTest1/13/flax_model.msgpack
-
curl -L -o flax_model.msgpack https://huggingface.co/TheLitttleThings/DiffusionTest1/resolve/main/13/flax_model.msgpack
852 MB
- Xet hash:
- 3447e4ac4b33661ede45f633f46ea57a8b1edc6979910d455ce4122ea4924323
- Size of remote file:
- 852 MB
- SHA256:
- 8af15b2801ee72b348cdb5770dbf25f4e5991e59a5cb029a8c944ca754d631d7
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.