Instructions to use VISAI-AI/nitibench-ccl-human-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-human-finetuned-bge-m3 with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("VISAI-AI/nitibench-ccl-human-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:
- 33d6e1097bc76d1a68d8da7654a33e9d777e1d49f1b0b25b334d3f3652e1084b
- Size of remote file:
- 2.27 GB
- SHA256:
- f1a25dbea7b458ee736bc1f4e6d0aa45fbe04368c7a17a183cb7f3b22eace641
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