Instructions to use splitner/single-qa-ontonotes with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use splitner/single-qa-ontonotes with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("splitner/single-qa-ontonotes") model = AutoModel.from_pretrained("splitner/single-qa-ontonotes", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from splitner/single-qa-ontonotes: direct link, hf CLI and curl.
- Browser
- Download file 2.03 kB
-
https://huggingface.co/splitner/single-qa-ontonotes/resolve/refs%2Fpr%2F1/training_args.bin
- Command line
-
hf download hf://splitner/single-qa-ontonotes@refs/pr/1/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/splitner/single-qa-ontonotes/resolve/refs%2Fpr%2F1/training_args.bin
2.03 kB
- Xet hash:
- e9c649feb417f178525a6dc002310f1c0ebb7d649ca7274530436e8aa820b890
- Size of remote file:
- 2.03 kB
- SHA256:
- 4b6cd93d9308f7c153e8a9fc58a24695d407643d8e9e713b520c6b1fb397caaf
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