Instructions to use harish/AStitchInLanguageModels-Task2_PT_mBERTTokenizedSelectReplacePreTrain with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use harish/AStitchInLanguageModels-Task2_PT_mBERTTokenizedSelectReplacePreTrain with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="harish/AStitchInLanguageModels-Task2_PT_mBERTTokenizedSelectReplacePreTrain")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("harish/AStitchInLanguageModels-Task2_PT_mBERTTokenizedSelectReplacePreTrain") model = AutoModelForMaskedLM.from_pretrained("harish/AStitchInLanguageModels-Task2_PT_mBERTTokenizedSelectReplacePreTrain", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from harish/AStitchInLanguageModels-Task2_PT_mBERTTokenizedSelectReplacePreTrain: direct link, hf CLI and curl.
- Browser
- Download file 2.48 kB
-
https://huggingface.co/harish/AStitchInLanguageModels-Task2_PT_mBERTTokenizedSelectReplacePreTrain/resolve/main/training_args.bin
- Command line
-
hf download hf://harish/AStitchInLanguageModels-Task2_PT_mBERTTokenizedSelectReplacePreTrain/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/harish/AStitchInLanguageModels-Task2_PT_mBERTTokenizedSelectReplacePreTrain/resolve/main/training_args.bin
2.48 kB
- Xet hash:
- b028d64b469fec229bd8ee40d0e0cd10bd7a958989ed2a741aadf0b52bfb7f0f
- Size of remote file:
- 2.48 kB
- SHA256:
- f11838fd60eff6dd3b83cfcaf28ed34ef20fcf19af37ad66cdd4b719326c12cc
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