Instructions to use vblagoje/greaselm-csqa with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use vblagoje/greaselm-csqa with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoModelForMultipleChoice model = AutoModelForMultipleChoice.from_pretrained("vblagoje/greaselm-csqa", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download matcher_patterns.json from vblagoje/greaselm-csqa: direct link, hf CLI and curl.
- Browser
- Download file 42.6 MB
-
https://huggingface.co/vblagoje/greaselm-csqa/resolve/main/matcher_patterns.json
- Command line
-
hf download hf://vblagoje/greaselm-csqa/matcher_patterns.json
-
curl -L -o matcher_patterns.json https://huggingface.co/vblagoje/greaselm-csqa/resolve/main/matcher_patterns.json
42.6 MB
- Xet hash:
- d780fe778cfb8b7116c596ad731897faa0fa8baadb3577005c5be565cb6b9b75
- Size of remote file:
- 42.6 MB
- SHA256:
- 52db9cfc86265ab16560d77284a9039df6763c3f94e556a020a283fc63f1cd19
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