Completed
BM25
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Classroom Contents
Mastering Retrieval for LLMs - BM25, Fine-tuned Embeddings, and Re-Rankers
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- 1 Mastering Retrieval RAG for LLMs
- 2 Video Overview
- 3 Baseline Performance with No Retrieval
- 4 Document Chunking - Naive vs Sentence based
- 5 BM25
- 6 Semantic / Vector / Embeddings Search
- 7 Cosine vs Dot Product Similarity
- 8 Generating Chunks and Embeddings
- 9 Running BM25 and Similarity Retrieval
- 10 Performance with BM25 vs Similarity
- 11 Fine-tuning embeddings / encoders
- 12 Preparing fine-tuning datasets
- 13 Embeddings Training Continued
- 14 Performance after Fine-tuning
- 15 Re-rankers
- 16 : Cross-encoders
- 17 LLM re-rankers
- 18 Re-ranking performance
- 19 Final Tips
