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:
- 63ad7db30c41a2a65df151f49e0f2a79022d8b565839c5d7ada4c5e8a71f01b1
- Size of remote file:
- 4.86 kB
- SHA256:
- 1023e2c29b277eca49824e756bca07880988f4f764313ea966fcdf49706e410a
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