Instructions to use alinankali/test_deploy with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use alinankali/test_deploy with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("alinankali/test_deploy", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download sentencepiece.bpe.model from alinankali/test_deploy: direct link, hf CLI and curl.
- Browser
- Download file 4.85 MB
-
https://huggingface.co/alinankali/test_deploy/resolve/main/sentencepiece.bpe.model
- Command line
-
hf download hf://alinankali/test_deploy/sentencepiece.bpe.model
-
curl -L -o sentencepiece.bpe.model https://huggingface.co/alinankali/test_deploy/resolve/main/sentencepiece.bpe.model
4.85 MB
- Xet hash:
- 5a49bb827da480c22c5bfab7f453b923b8e7f4624f3d1f1672e130e59f6016aa
- Size of remote file:
- 4.85 MB
- SHA256:
- 14bb8dfb35c0ffdea7bc01e56cea38b9e3d5efcdcb9c251d6b40538e1aab555a
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.