Instructions to use CannLiew/cpmi with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use CannLiew/cpmi with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="CannLiew/cpmi", trust_remote_code=True)# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("CannLiew/cpmi", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from CannLiew/cpmi: direct link, hf CLI and curl.
- Browser
- Download file 4.16 kB
-
https://huggingface.co/CannLiew/cpmi/resolve/main/training_args.bin
- Command line
-
hf download hf://CannLiew/cpmi/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/CannLiew/cpmi/resolve/main/training_args.bin
4.16 kB
- Xet hash:
- e5057d34cc54ff1065172f4e3f10d5cf831a52043b8b5fbccf0e957c71f77a72
- Size of remote file:
- 4.16 kB
- SHA256:
- a1ca5b8c009d18feb552d5a501f194680a1ed2747344305d4eeca9fa7b484ceb
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.