Instructions to use SoTrxII/analytical-pattern-embedder with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use SoTrxII/analytical-pattern-embedder with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("SoTrxII/analytical-pattern-embedder") 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
File size: 1,325 Bytes
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"__version__": {
"pytorch": "2.14.1+cpu",
"sentence_transformers": "6.1.0",
"transformers": "5.19.0"
},
"default_prompt_name": null,
"model_type": "SentenceTransformer",
"prompts": {
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"Classification": "task: classification | query: ",
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"FactChecking": "task: fact checking | query: ",
"InstructionRetrieval": "task: code retrieval | query: ",
"MultilabelClassification": "task: classification | query: ",
"PairClassification": "task: sentence similarity | query: ",
"QuestionAnswering": "task: question answering | query: ",
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"STS": "task: sentence similarity | query: ",
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"SentenceSimilarity": "task: sentence similarity | query: ",
"Summarization": "task: sentence similarity | query: ",
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"similarity_fn_name": "cosine"
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