Instructions to use harish/AStitchInLanguageModels-Task2_PT_mBERTTokenizedALLReplacePreTrain with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use harish/AStitchInLanguageModels-Task2_PT_mBERTTokenizedALLReplacePreTrain with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="harish/AStitchInLanguageModels-Task2_PT_mBERTTokenizedALLReplacePreTrain")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("harish/AStitchInLanguageModels-Task2_PT_mBERTTokenizedALLReplacePreTrain") model = AutoModelForMaskedLM.from_pretrained("harish/AStitchInLanguageModels-Task2_PT_mBERTTokenizedALLReplacePreTrain", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from harish/AStitchInLanguageModels-Task2_PT_mBERTTokenizedALLReplacePreTrain: direct link, hf CLI and curl.
- Browser
- Download file 712 MB
-
https://huggingface.co/harish/AStitchInLanguageModels-Task2_PT_mBERTTokenizedALLReplacePreTrain/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://harish/AStitchInLanguageModels-Task2_PT_mBERTTokenizedALLReplacePreTrain/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/harish/AStitchInLanguageModels-Task2_PT_mBERTTokenizedALLReplacePreTrain/resolve/main/pytorch_model.bin
712 MB
- Xet hash:
- 7dadd5ade06f2329413ccc237b99691f4dac7ce8a6eccd24eb7566fe4e4e4d63
- Size of remote file:
- 712 MB
- SHA256:
- 498f6ce6e1432cfac274dae60fb01b6dedf6b4dcd968e155cc9f8c1cf624afa8
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