Instructions to use splitner/spanclass-qa-crossentropy-wnut17 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use splitner/spanclass-qa-crossentropy-wnut17 with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("splitner/spanclass-qa-crossentropy-wnut17") model = AutoModel.from_pretrained("splitner/spanclass-qa-crossentropy-wnut17", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from splitner/spanclass-qa-crossentropy-wnut17: direct link, hf CLI and curl.
- Browser
- Download file 438 MB
-
https://huggingface.co/splitner/spanclass-qa-crossentropy-wnut17/resolve/refs%2Fpr%2F1/pytorch_model.bin
- Command line
-
hf download hf://splitner/spanclass-qa-crossentropy-wnut17@refs/pr/1/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/splitner/spanclass-qa-crossentropy-wnut17/resolve/refs%2Fpr%2F1/pytorch_model.bin
438 MB
- Xet hash:
- b2a7615eb0dc05f1fe2e8d72be261772353e09b1c27ee8b73ccdd4344c5638cf
- Size of remote file:
- 438 MB
- SHA256:
- 2b845fabdfff9eee57755d4821803dbf5602e16267f7c6257cb876893bb61bd7
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