Instructions to use graviraja/covidbert_squad with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use graviraja/covidbert_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="graviraja/covidbert_squad")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("graviraja/covidbert_squad") model = AutoModelForQuestionAnswering.from_pretrained("graviraja/covidbert_squad", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download flax_model.msgpack from graviraja/covidbert_squad: direct link, hf CLI and curl.
- Browser
- Download file 436 MB
-
https://huggingface.co/graviraja/covidbert_squad/resolve/main/flax_model.msgpack
- Command line
-
hf download hf://graviraja/covidbert_squad/flax_model.msgpack
-
curl -L -o flax_model.msgpack https://huggingface.co/graviraja/covidbert_squad/resolve/main/flax_model.msgpack
436 MB
- Xet hash:
- 039728694bf449c65a0567a20ac4c16760fdc811087ee0c3a59d7a14493fec4a
- Size of remote file:
- 436 MB
- SHA256:
- 6fcf0a7dcdc117df0dffd7c206f84853524680076d7ac719d0bca0484e3a38e9
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