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 preprocessor_config.json from vblagoje/greaselm-csqa: direct link, hf CLI and curl.
- Browser
- Download file 251 Bytes
-
https://huggingface.co/vblagoje/greaselm-csqa/resolve/main/preprocessor_config.json
- Command line
-
hf download hf://vblagoje/greaselm-csqa/preprocessor_config.json
-
curl -L -o preprocessor_config.json https://huggingface.co/vblagoje/greaselm-csqa/resolve/main/preprocessor_config.json
251 Bytes
| { | |
| "cpnet_vocab_path": "concept.txt", | |
| "pattern_path": "matcher_patterns.json", | |
| "pruned_graph_path": "conceptnet_en_pruned.pickle.gz", | |
| "score_model": "distilroberta-base", | |
| "feature_extractor_type": "GreaseLMFeatureExtractor", | |
| "max_node_num": 200 | |
| } |