Instructions to use splitner/single-qa-wnut17 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use splitner/single-qa-wnut17 with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("splitner/single-qa-wnut17") model = AutoModel.from_pretrained("splitner/single-qa-wnut17", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from splitner/single-qa-wnut17: direct link, hf CLI and curl.
- Browser
- Download file 2.1 kB
-
https://huggingface.co/splitner/single-qa-wnut17/resolve/main/training_args.bin
- Command line
-
hf download hf://splitner/single-qa-wnut17/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/splitner/single-qa-wnut17/resolve/main/training_args.bin
2.1 kB
- Xet hash:
- f70e17f3cbd564bb52bfe70e3eca52c57a5ea757aae7c4744187825cd5eee25a
- Size of remote file:
- 2.1 kB
- SHA256:
- 24376c2c378226fdb9a02eea7dd3318be1db7d76cdb3d941bf505d64b16108a4
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