Instructions to use harish/AStitchInLanguageModels-Task2_EN_SentTransTokenizedNoPreTrain with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use harish/AStitchInLanguageModels-Task2_EN_SentTransTokenizedNoPreTrain with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("harish/AStitchInLanguageModels-Task2_EN_SentTransTokenizedNoPreTrain", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download 0_Transformer/pytorch_model.bin from harish/AStitchInLanguageModels-Task2_EN_SentTransTokenizedNoPreTrain: direct link, hf CLI and curl.
- Browser
- Download file 433 MB
-
https://huggingface.co/harish/AStitchInLanguageModels-Task2_EN_SentTransTokenizedNoPreTrain/resolve/main/0_Transformer/pytorch_model.bin
- Command line
-
hf download hf://harish/AStitchInLanguageModels-Task2_EN_SentTransTokenizedNoPreTrain/0_Transformer/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/harish/AStitchInLanguageModels-Task2_EN_SentTransTokenizedNoPreTrain/resolve/main/0_Transformer/pytorch_model.bin
433 MB
- Xet hash:
- 8a497289c6bd8ff8251c17f726c00947a1f8aa77ecbb076ff76263885433a4fb
- Size of remote file:
- 433 MB
- SHA256:
- 1ee60b248a71d83d4cf31b1a846a097cc76c71e36a99a53260d2275383f84266
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.