Instructions to use splitner/single-seqtag-bionlp13cg with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use splitner/single-seqtag-bionlp13cg with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("splitner/single-seqtag-bionlp13cg") model = AutoModel.from_pretrained("splitner/single-seqtag-bionlp13cg", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from splitner/single-seqtag-bionlp13cg: direct link, hf CLI and curl.
- Browser
- Download file 468 MB
-
https://huggingface.co/splitner/single-seqtag-bionlp13cg/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://splitner/single-seqtag-bionlp13cg/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/splitner/single-seqtag-bionlp13cg/resolve/main/pytorch_model.bin
468 MB
- Xet hash:
- 9cb5ce33faa1f53b8c64ce0cf666a7f56d00f98af96899a4b1f395d38e27ef4d
- Size of remote file:
- 468 MB
- SHA256:
- b146d2877b5c1932dc9533dc4f7b2019a24cdd0bc8b1c2f0f57389e43174937e
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