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 training_args.bin from splitner/spanclass-qa-dice-ontonotes: direct link, hf CLI and curl.
- Browser
- Download file 1.97 kB
-
https://huggingface.co/splitner/spanclass-qa-dice-ontonotes/resolve/main/training_args.bin
- Command line
-
hf download hf://splitner/spanclass-qa-dice-ontonotes/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/splitner/spanclass-qa-dice-ontonotes/resolve/main/training_args.bin
1.97 kB
- Xet hash:
- a5588e99af2395171cdb46711f04064f41386df9f36c71a57a65f3ffc78fb40c
- Size of remote file:
- 1.97 kB
- SHA256:
- 5b06cfa9e4eb49fd9e2d57c3637beeba6c754e04bbc4442ecd914daa087ba8cb
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