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 optimizer.pt from splitner/spanclass-qa-crossentropy-wnut17: direct link, hf CLI and curl.
- Browser
- Download file 876 MB
-
https://huggingface.co/splitner/spanclass-qa-crossentropy-wnut17/resolve/refs%2Fpr%2F1/optimizer.pt
- Command line
-
hf download hf://splitner/spanclass-qa-crossentropy-wnut17@refs/pr/1/optimizer.pt
-
curl -L -o optimizer.pt https://huggingface.co/splitner/spanclass-qa-crossentropy-wnut17/resolve/refs%2Fpr%2F1/optimizer.pt
876 MB
- Xet hash:
- 84668d2b8122bfad54971035863703f333d30c79d19ebc6d241fe7fd75431dfc
- Size of remote file:
- 876 MB
- SHA256:
- af15c9fab49a9c602218bdc17305d3737754c4342cfdc4fd826c20bd7d461361
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