Instructions to use splitner/spanclass-qa-dice-wnut17 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use splitner/spanclass-qa-dice-wnut17 with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("splitner/spanclass-qa-dice-wnut17") model = AutoModel.from_pretrained("splitner/spanclass-qa-dice-wnut17", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from splitner/spanclass-qa-dice-wnut17: direct link, hf CLI and curl.
- Browser
- Download file 2.1 kB
-
https://huggingface.co/splitner/spanclass-qa-dice-wnut17/resolve/refs%2Fpr%2F1/training_args.bin
- Command line
-
hf download hf://splitner/spanclass-qa-dice-wnut17@refs/pr/1/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/splitner/spanclass-qa-dice-wnut17/resolve/refs%2Fpr%2F1/training_args.bin
2.1 kB
- Xet hash:
- 073e19de320d2aac733306b46013ce68af43b00fc5c5a6a0eba3a2203e3a886c
- Size of remote file:
- 2.1 kB
- SHA256:
- a13884b1a332024118b685658d5d797ccd7833dcb17ecd0378054bde1c95ff0f
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