sentence-transformers
Safetensors
bert
retrieval
movie-recommendation
semantic-search
Eval Results (legacy)
Instructions to use JJTsao/fine-tuned_movie_retriever-all-minilm-l6-v2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use JJTsao/fine-tuned_movie_retriever-all-minilm-l6-v2 with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("JJTsao/fine-tuned_movie_retriever-all-minilm-l6-v2") 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:
- 5d03fb1e39624db9ba14c0a8b10d96327193cc8d01545f4c47f7b7a210776273
- Size of remote file:
- 90.9 MB
- SHA256:
- 985c046eb9305d68ae80b0da47a81fc551d59bb2fcf54e7e051cc1e24defb3a0
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