Instructions to use jtz18/bert-finetuned-squad with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use jtz18/bert-finetuned-squad with Transformers:
# Use a pipeline as a high-level helper # Warning: Pipeline type "question-answering" is no longer supported in transformers v5. # You must load the model directly (see below) or downgrade to v4.x with: # pip install "transformers<5.0.0" from transformers import pipeline pipe = pipeline("question-answering", model="jtz18/bert-finetuned-squad")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("jtz18/bert-finetuned-squad") model = AutoModelForQuestionAnswering.from_pretrained("jtz18/bert-finetuned-squad", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from jtz18/bert-finetuned-squad: direct link, hf CLI and curl.
- Browser
- Download file 5.11 kB
-
https://huggingface.co/jtz18/bert-finetuned-squad/resolve/main/training_args.bin
- Command line
-
hf download hf://jtz18/bert-finetuned-squad/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/jtz18/bert-finetuned-squad/resolve/main/training_args.bin
5.11 kB
- Xet hash:
- d332fc6942b1d9bec5c1de9c66c8cc87490ad96bb262a92a45822098e25ccb36
- Size of remote file:
- 5.11 kB
- SHA256:
- c08e7264b98f0f845fc924da6c5f20c0e80263ba7aa059f2e82011e150bbb6a7
路
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