Instructions to use datauma/bert-finetuned-squad with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use datauma/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="datauma/bert-finetuned-squad")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("datauma/bert-finetuned-squad") model = AutoModelForQuestionAnswering.from_pretrained("datauma/bert-finetuned-squad", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tf_model.h5 from datauma/bert-finetuned-squad: direct link, hf CLI and curl.
- Browser
- Download file 431 MB
-
https://huggingface.co/datauma/bert-finetuned-squad/resolve/main/tf_model.h5
- Command line
-
hf download hf://datauma/bert-finetuned-squad/tf_model.h5
-
curl -L -o tf_model.h5 https://huggingface.co/datauma/bert-finetuned-squad/resolve/main/tf_model.h5
431 MB
- Xet hash:
- 8a4cad16dacf757fd208770a2f766e077ad5495b5d8324663be896a6a1f912c8
- Size of remote file:
- 431 MB
- SHA256:
- ae375ba11d691998c3b5ee0809cfb4da76b8e45ba34c3b00080fba7460cd1c15
路
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