Instructions to use deepset/tapas-large-nq-hn-reader with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use deepset/tapas-large-nq-hn-reader with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, TapasForScoredQA tokenizer = AutoTokenizer.from_pretrained("deepset/tapas-large-nq-hn-reader") model = TapasForScoredQA.from_pretrained("deepset/tapas-large-nq-hn-reader", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from deepset/tapas-large-nq-hn-reader: direct link, hf CLI and curl.
- Browser
- Download file 1.35 GB
-
https://huggingface.co/deepset/tapas-large-nq-hn-reader/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://deepset/tapas-large-nq-hn-reader/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/deepset/tapas-large-nq-hn-reader/resolve/main/pytorch_model.bin
1.35 GB
- Xet hash:
- 4c9bb7b00792885007f0a4e9217a1f7f5ce18d3d0e37139ca3f8814ef325c7fd
- Size of remote file:
- 1.35 GB
- SHA256:
- cb42127a4220d52008970650993509dd67194b8a47bb9e7ffb4c8eb7d8b22cc9
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