Instructions to use harish/AStitchInLanguageModels-Task2_EN_BERTTokenizedSelectReplacePreTrain with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use harish/AStitchInLanguageModels-Task2_EN_BERTTokenizedSelectReplacePreTrain with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="harish/AStitchInLanguageModels-Task2_EN_BERTTokenizedSelectReplacePreTrain")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("harish/AStitchInLanguageModels-Task2_EN_BERTTokenizedSelectReplacePreTrain") model = AutoModelForMaskedLM.from_pretrained("harish/AStitchInLanguageModels-Task2_EN_BERTTokenizedSelectReplacePreTrain", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download optimizer.pt from harish/AStitchInLanguageModels-Task2_EN_BERTTokenizedSelectReplacePreTrain: direct link, hf CLI and curl.
- Browser
- Download file 867 MB
-
https://huggingface.co/harish/AStitchInLanguageModels-Task2_EN_BERTTokenizedSelectReplacePreTrain/resolve/main/optimizer.pt
- Command line
-
hf download hf://harish/AStitchInLanguageModels-Task2_EN_BERTTokenizedSelectReplacePreTrain/optimizer.pt
-
curl -L -o optimizer.pt https://huggingface.co/harish/AStitchInLanguageModels-Task2_EN_BERTTokenizedSelectReplacePreTrain/resolve/main/optimizer.pt
867 MB
- Xet hash:
- e5b31e0f677975c7cdf40bb123e58c40e5ece36281555cc17df8c1899af1dd0d
- Size of remote file:
- 867 MB
- SHA256:
- 9ea8d37c60696a573bf264f8da4eab520f9a92a3e2b1125183e4a54fffb21351
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