Instructions to use ToluClassics/extractive_reader_nq_squad_v2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ToluClassics/extractive_reader_nq_squad_v2 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="ToluClassics/extractive_reader_nq_squad_v2")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("ToluClassics/extractive_reader_nq_squad_v2") model = AutoModelForQuestionAnswering.from_pretrained("ToluClassics/extractive_reader_nq_squad_v2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from ToluClassics/extractive_reader_nq_squad_v2: direct link, hf CLI and curl.
- Browser
- Download file 667 MB
-
https://huggingface.co/ToluClassics/extractive_reader_nq_squad_v2/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://ToluClassics/extractive_reader_nq_squad_v2/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/ToluClassics/extractive_reader_nq_squad_v2/resolve/main/pytorch_model.bin
667 MB
- Xet hash:
- 7dbd15af2425dc7a0a72b6b33ee398b412d86f14c78a0ac5b040c83a6a7e4b10
- Size of remote file:
- 667 MB
- SHA256:
- d21f442030e484a21bd34ed4178efb86cacb488a0e4857b68549ef8f708b3baa
路
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