Instructions to use vesteinn/IceBERT-QA with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use vesteinn/IceBERT-QA 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="vesteinn/IceBERT-QA")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("vesteinn/IceBERT-QA") model = AutoModelForQuestionAnswering.from_pretrained("vesteinn/IceBERT-QA", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from vesteinn/IceBERT-QA: direct link, hf CLI and curl.
- Browser
- Download file 496 MB
-
https://huggingface.co/vesteinn/IceBERT-QA/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://vesteinn/IceBERT-QA/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/vesteinn/IceBERT-QA/resolve/main/pytorch_model.bin
496 MB
- Xet hash:
- ee58c178f6ca2d2f8226cf23b6404f7d7a01fc0a69295009d202a62c23ae58b7
- Size of remote file:
- 496 MB
- SHA256:
- cbc820a1effd0e0e8999ad148ef36a7fcb25f9a32a167a23d758cf33ca403a81
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