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 training_args.bin from harish/AStitchInLanguageModels-Task2_PT_mBERTTokenizedALLReplacePreTrain: direct link, hf CLI and curl.
- Browser
- Download file 2.48 kB
-
https://huggingface.co/harish/AStitchInLanguageModels-Task2_PT_mBERTTokenizedALLReplacePreTrain/resolve/main/training_args.bin
- Command line
-
hf download hf://harish/AStitchInLanguageModels-Task2_PT_mBERTTokenizedALLReplacePreTrain/training_args.bin
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curl -L -o training_args.bin https://huggingface.co/harish/AStitchInLanguageModels-Task2_PT_mBERTTokenizedALLReplacePreTrain/resolve/main/training_args.bin
2.48 kB
- Xet hash:
- be1dc6e70d9772ef06b3f821c2be38446eaee1ca000cbcaf650103b9d3299afa
- Size of remote file:
- 2.48 kB
- SHA256:
- f4b128f7a75d9471494063dd9a46f908885ba4c231f43237f0d01ed0b42ec7d6
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