Instructions to use VISAI-AI/nitibench-ccl-auto-finetuned-bge-m3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use VISAI-AI/nitibench-ccl-auto-finetuned-bge-m3 with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("VISAI-AI/nitibench-ccl-auto-finetuned-bge-m3") sentences = [ "The weather is lovely today.", "It's so sunny outside!", "He drove to the stadium." ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [3, 3] - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 586b281e406952e7ae8716f4d0f862d71084b2495cc3cceef8c445e4a4c379da
- Size of remote file:
- 4.2 MB
- SHA256:
- 34f6bb891527710560250f0301e6543172ed75f16c0e050569d46b1a8dffe50b
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