Instructions to use harish/AStitchInLanguageModels-Task2_EN_BERTTokenizedALLReplacePreTrain with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use harish/AStitchInLanguageModels-Task2_EN_BERTTokenizedALLReplacePreTrain with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="harish/AStitchInLanguageModels-Task2_EN_BERTTokenizedALLReplacePreTrain")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("harish/AStitchInLanguageModels-Task2_EN_BERTTokenizedALLReplacePreTrain") model = AutoModelForMaskedLM.from_pretrained("harish/AStitchInLanguageModels-Task2_EN_BERTTokenizedALLReplacePreTrain", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from harish/AStitchInLanguageModels-Task2_EN_BERTTokenizedALLReplacePreTrain: direct link, hf CLI and curl.
- Browser
- Download file 433 MB
-
https://huggingface.co/harish/AStitchInLanguageModels-Task2_EN_BERTTokenizedALLReplacePreTrain/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://harish/AStitchInLanguageModels-Task2_EN_BERTTokenizedALLReplacePreTrain/pytorch_model.bin
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curl -L -o pytorch_model.bin https://huggingface.co/harish/AStitchInLanguageModels-Task2_EN_BERTTokenizedALLReplacePreTrain/resolve/main/pytorch_model.bin
433 MB
- Xet hash:
- 00045456f87672fc5a4d09a5ceb1b9988c675db4d6006295dfb4a189af97cff0
- Size of remote file:
- 433 MB
- SHA256:
- 0ca7efdfb7ad4b16391ce21c1e2f5051984a61cbe9a6108afbb6351503463106
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