Instructions to use splitner/spandetect-seqtag-wnut17 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use splitner/spandetect-seqtag-wnut17 with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("splitner/spandetect-seqtag-wnut17") model = AutoModel.from_pretrained("splitner/spandetect-seqtag-wnut17", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from splitner/spandetect-seqtag-wnut17: direct link, hf CLI and curl.
- Browser
- Download file 466 MB
-
https://huggingface.co/splitner/spandetect-seqtag-wnut17/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://splitner/spandetect-seqtag-wnut17/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/splitner/spandetect-seqtag-wnut17/resolve/main/pytorch_model.bin
466 MB
- Xet hash:
- 4eb2d3e238e644737c9f6cb7abf4fcce53ff2f5021610192b886330c9de35472
- Size of remote file:
- 466 MB
- SHA256:
- 08ab5421b9c0180db29bdb58f068fd7c525b820c2a64658e387b436ab3131d3b
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