Instructions to use Xikun/greaselm-obqa with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Xikun/greaselm-obqa with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoModelForMultipleChoice model = AutoModelForMultipleChoice.from_pretrained("Xikun/greaselm-obqa", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download matcher_patterns.json from Xikun/greaselm-obqa: direct link, hf CLI and curl.
- Browser
- Download file 42.6 MB
-
https://huggingface.co/Xikun/greaselm-obqa/resolve/main/matcher_patterns.json
- Command line
-
hf download hf://Xikun/greaselm-obqa/matcher_patterns.json
-
curl -L -o matcher_patterns.json https://huggingface.co/Xikun/greaselm-obqa/resolve/main/matcher_patterns.json
42.6 MB
- Xet hash:
- 52871c57be759a241fa1e43ff6441afd5c64a4637548c7b2b2cedb50b62bc99b
- Size of remote file:
- 42.6 MB
- SHA256:
- 52db9cfc86265ab16560d77284a9039df6763c3f94e556a020a283fc63f1cd19
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