Instructions to use splitner/spanclass-qa-dice-ontonotes with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use splitner/spanclass-qa-dice-ontonotes with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("splitner/spanclass-qa-dice-ontonotes") model = AutoModel.from_pretrained("splitner/spanclass-qa-dice-ontonotes", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download scheduler.pt from splitner/spanclass-qa-dice-ontonotes: direct link, hf CLI and curl.
- Browser
- Download file 623 Bytes
-
https://huggingface.co/splitner/spanclass-qa-dice-ontonotes/resolve/main/scheduler.pt
- Command line
-
hf download hf://splitner/spanclass-qa-dice-ontonotes/scheduler.pt
-
curl -L -o scheduler.pt https://huggingface.co/splitner/spanclass-qa-dice-ontonotes/resolve/main/scheduler.pt
623 Bytes
- Xet hash:
- d19fe4dfb3df8dbc7ce1c555209d40d1f58f75c2a3838df92a0f7bb67b18b8f8
- Size of remote file:
- 623 Bytes
- SHA256:
- 3ff077b6829b1bd4e8216d57579bdb9135780ec15cd8016bcbfcecdc00a7010d
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