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:
- 661dff0b5583de8a2b851cfa22058cb9100480578f4686f9d4f5df785706f6cf
- Size of remote file:
- 1.21 kB
- SHA256:
- 1a62d32990f5a70bc24f8d2b4b5cc34c952b075f4e9c395c5224f258103e14ec
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