Sentence Similarity
sentence-transformers
Safetensors
English
mpnet
text2sql
schema-linking
aap-sql
text-embeddings-inference
Instructions to use TommyPanLab/AAP-SQL-E2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use TommyPanLab/AAP-SQL-E2 with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("TommyPanLab/AAP-SQL-E2") sentences = [ "That is a happy person", "That is a happy dog", "That is a very happy person", "Today is a sunny day" ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [4, 4] - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 6e2e4a5273da3bf7f971a1163ce557f91554bd6a69924893b6f8d477332954f5
- Size of remote file:
- 438 MB
- SHA256:
- 28f5610b924a7ef83849327c794072c0d27535d07e132fa99a4591b83cd50dcc
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