Instructions to use splitner/single-seqtag-ontonotes with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use splitner/single-seqtag-ontonotes with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("splitner/single-seqtag-ontonotes") model = AutoModel.from_pretrained("splitner/single-seqtag-ontonotes", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from splitner/single-seqtag-ontonotes: direct link, hf CLI and curl.
- Browser
- Download file 525 MB
-
https://huggingface.co/splitner/single-seqtag-ontonotes/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://splitner/single-seqtag-ontonotes/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/splitner/single-seqtag-ontonotes/resolve/main/pytorch_model.bin
525 MB
- Xet hash:
- 7863c3a046915c5d2f7539bf983f3a77e7f6cdab5c1924a8e3a96dfd87298a61
- Size of remote file:
- 525 MB
- SHA256:
- 6e8d8e9ec75d7ecf979a8d7e408deb072dd7de54f51e36c90402136df4d0d6ae
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