mteb-retrieve
OfficialEmbedding retrieval and semantic ranking.
Authorletta-ai
Version1.0.0
Installs0
System Documentation
What problem does it solve?
This Skill guides text embedding retrieval tasks, including encoding documents, computing similarities, and ranking documents by semantic similarity.
Core Features & Use Cases
- Model loading & encoding: Use sentence-transformers to encode documents and query.
- Similarity computation: Cosine similarity to rank documents by relevance.
- Retrieval & verification: Retrieve top-k results and verify semantic alignment.
Quick Start
Example: encode a set of documents and a query, then retrieve the top-5 most similar documents by cosine similarity.
Dependency Matrix
Required Modules
None requiredComponents
references
💻 Claude Code Installation
Recommended: Let Claude install automatically. Simply copy and paste the text below to Claude Code.
Please help me install this Skill: Name: mteb-retrieve Download link: https://github.com/letta-ai/skills/archive/main.zip#mteb-retrieve Please download this .zip file, extract it, and install it in the .claude/skills/ directory.
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