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BGE

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  • Introduction
  • BGE
  • Tutorials
  • API
    • FAQ
    • Community
    • HF Models
  • GitHub
  • PyPI
  • HF Models
  • Home
  • Introduction
  • BGE
  • Tutorials
  • API
  • FAQ
  • Community
  • HF Models
  • GitHub
  • PyPI
  • HF Models

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Tutorials

  • 1. Embedding
    • Intro to Embedding
    • BGE Series
    • BGE Auto Embedder
    • BGE Explanation
    • BGE-M3
    • BGE-EN-ICL
  • 2. Metrics
    • Similarity
    • Evaluation Metrics
  • 3. Indexing
    • Indexing Using Faiss
    • Faiss GPU
    • Faiss Indexes
    • Faiss Quantizers
    • Choosing Index
  • 4. Evaluation
    • Evaluation
    • MTEB
    • MTEB Leaderboard
    • C-MTEB
    • Evaluation Using Sentence Transformers
    • Evaluate on BEIR
    • Evaluate on MIRACL
    • Evaluate on MLDR
  • 5. Reranking
    • Reranker
    • BGE Reranker
    • Evaluate Reranker
  • 6. RAG
    • Simple RAG From Scratch
    • RAG with LangChain
    • RAG with LlamaIndex
  • 7. Finetuning
    • Data Preparation for Fine-tuning
    • Fine-tuning
    • Evaluate the Fine-tuned Model
    • Hard Negatives
  • Tutorials

Tutorials#

In this section, we provide hands on introduction to different topics that highly related to embedding models and retrieval.

To run the tutorials, clone the GitHub repo and check the Tutorials folder.

Tutorials

  • 1. Embedding
  • 2. Metrics
  • 3. Indexing
  • 4. Evaluation
  • 5. Reranking
  • 6. RAG
  • 7. Finetuning

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