Instructions to use prithivida/flashrank with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use prithivida/flashrank with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("prithivida/flashrank", dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 4edfc9934a4936318bf15506213843a4ca841973214ea5a505a79776c213721b
- Size of remote file:
- 492 MB
- SHA256:
- 8cffd708972a58aed0cdb6ef99d358d637ba604112b9ad28ae561f7e168d2446
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