Sentence Similarity
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sentence-transformers
English
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feature-extraction
embedding
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retrieval
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scientific-search
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Instructions to use LinerAI/snowflake-arctic-embed-m-v2.0-academic with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use LinerAI/snowflake-arctic-embed-m-v2.0-academic with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("LinerAI/snowflake-arctic-embed-m-v2.0-academic", trust_remote_code=True, dtype="auto") - sentence-transformers
How to use LinerAI/snowflake-arctic-embed-m-v2.0-academic with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("LinerAI/snowflake-arctic-embed-m-v2.0-academic", trust_remote_code=True) 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
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