Instructions to use splitner/single-qa-ontonotes with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use splitner/single-qa-ontonotes with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("splitner/single-qa-ontonotes") model = AutoModel.from_pretrained("splitner/single-qa-ontonotes", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from splitner/single-qa-ontonotes: direct link, hf CLI and curl.
- Browser
- Download file 525 MB
-
https://huggingface.co/splitner/single-qa-ontonotes/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://splitner/single-qa-ontonotes/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/splitner/single-qa-ontonotes/resolve/main/pytorch_model.bin
525 MB
- Xet hash:
- 6297515d52f82009739f9adeb63c5f669fb289cbadc52c4f3020996b1a1e61e4
- Size of remote file:
- 525 MB
- SHA256:
- 3c6ab4ff164aa6889dd25cb3e09adbd1f4c7fe1db78ba985aa19ac8214470ffd
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