Instructions to use spacemanidol/msmarco_colbert_summary_enhanced with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use spacemanidol/msmarco_colbert_summary_enhanced with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="spacemanidol/msmarco_colbert_summary_enhanced")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("spacemanidol/msmarco_colbert_summary_enhanced") model = AutoModel.from_pretrained("spacemanidol/msmarco_colbert_summary_enhanced", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- e618b80387ebeae943530ba019ab30a2e6a8614ae6667dc182ec26b3fc7c8550
- Size of remote file:
- 438 MB
- SHA256:
- 86a35662b71abc73b129206b9b066fcbe146a3562010608aa867e13a22470617
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