Sentence Similarity
sentence-transformers
English
zephyr
zephyr-rtos
rag
retrieval
faiss
documentation
embedded
qwen
offline
Instructions to use eoinedge/zephyrproject with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use eoinedge/zephyrproject with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("eoinedge/zephyrproject") 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
Zephyr docs RAG index and tooling
Browse files- index/meta.json +8 -0
index/meta.json
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{
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"embedding_model": "sentence-transformers/all-MiniLM-L6-v2",
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"dimensions": 384,
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"chunks": 6949,
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"documents": 824,
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"index": "IndexFlatIP (cosine over normalised vectors)",
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"source": "repository: https://github.com/zephyrproject-rtos/zephyr.git\nref: main\ncommit: 580547d\nfiles: 829\n"
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}
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