Instructions to use harish/AStitchInLanguageModels-Task2_PT_mBERTTokenizedNoPreTrain with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use harish/AStitchInLanguageModels-Task2_PT_mBERTTokenizedNoPreTrain with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="harish/AStitchInLanguageModels-Task2_PT_mBERTTokenizedNoPreTrain")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("harish/AStitchInLanguageModels-Task2_PT_mBERTTokenizedNoPreTrain") model = AutoModelForMaskedLM.from_pretrained("harish/AStitchInLanguageModels-Task2_PT_mBERTTokenizedNoPreTrain", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from harish/AStitchInLanguageModels-Task2_PT_mBERTTokenizedNoPreTrain: direct link, hf CLI and curl.
- Browser
- Download file 712 MB
-
https://huggingface.co/harish/AStitchInLanguageModels-Task2_PT_mBERTTokenizedNoPreTrain/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://harish/AStitchInLanguageModels-Task2_PT_mBERTTokenizedNoPreTrain/pytorch_model.bin
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curl -L -o pytorch_model.bin https://huggingface.co/harish/AStitchInLanguageModels-Task2_PT_mBERTTokenizedNoPreTrain/resolve/main/pytorch_model.bin
712 MB
- Xet hash:
- 4dc725e4f708f29d97784d75d3ccf7bd07f6d8be8704320918b60a1ccbc3c70a
- Size of remote file:
- 712 MB
- SHA256:
- b1ca0c2da6704efb02a5b01c287d7d609cc23d5136e8be7d2152781ac33465cf
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