From 9801aa581b75e2ac51d500c3f2198c8f2f708422 Mon Sep 17 00:00:00 2001 From: yichuan520030910320 Date: Sat, 9 Aug 2025 21:33:33 -0700 Subject: [PATCH] [Readme]update embedding model config according to reddit feedback --- README.md | 2 +- docs/configuration-guide.md | 8 +++++++- 2 files changed, 8 insertions(+), 2 deletions(-) diff --git a/README.md b/README.md index 748b252..d53f818 100755 --- a/README.md +++ b/README.md @@ -189,7 +189,7 @@ All RAG examples share these common parameters. **Interactive mode** is availabl --force-rebuild # Force rebuild index even if it exists # Embedding Parameters ---embedding-model MODEL # e.g., facebook/contriever, text-embedding-3-small, nomic-embed-text, or mlx-community/multilingual-e5-base-mlx +--embedding-model MODEL # e.g., facebook/contriever, text-embedding-3-small, nomic-embed-text, mlx-community/Qwen3-Embedding-0.6B-8bit or nomic-embed-text --embedding-mode MODE # sentence-transformers, openai, mlx, or ollama # LLM Parameters (Text generation models) diff --git a/docs/configuration-guide.md b/docs/configuration-guide.md index 95cb3f0..22dcaa8 100644 --- a/docs/configuration-guide.md +++ b/docs/configuration-guide.md @@ -222,9 +222,15 @@ python apps/document_rag.py --query "What are the main techniques LEANN explores 3. **Use MLX on Apple Silicon** (optional optimization): ```bash - --embedding-mode mlx --embedding-model mlx-community/multilingual-e5-base-mlx + --embedding-mode mlx --embedding-model mlx-community/Qwen3-Embedding-0.6B-8bit ``` + MLX might not be the best choice, as we tested and found that it only offers 1.3x acceleration compared to HF, so maybe using ollama is a better choice for embedding generation +4. **Use Ollama** + ```bash + --embedding-mode ollama --embedding-model nomic-embed-text + ``` + To discover additional embedding models in ollama, check out https://ollama.com/search?c=embedding or read more about embedding models at https://ollama.com/blog/embedding-models, please do check the model size that works best for you ### If Search Quality is Poor 1. **Increase retrieval count**: