# FAQ ## 1. My building time seems long You can speed up the process by using a lightweight embedding model. Add this to your arguments: ```bash --embedding-model sentence-transformers/all-MiniLM-L6-v2 ``` **Model sizes:** `all-MiniLM-L6-v2` (30M parameters), `facebook/contriever` (~100M parameters), `Qwen3-0.6B` (600M parameters) ## 2. When should I use prompt templates? **Use prompt templates ONLY with task-specific embedding models** like Google's EmbeddingGemma. These models are specially trained to use different prompts for documents vs queries. **DO NOT use with regular models** like `nomic-embed-text`, `text-embedding-3-small`, or `bge-base-en-v1.5` - adding prompts to these models will corrupt the embeddings. **Example usage with EmbeddingGemma:** ```bash # Build with document prompt leann build my-docs --embedding-prompt-template "title: none | text: " # Search with query prompt leann search my-docs --query "your question" --embedding-prompt-template "task: search result | query: " ``` See the [Configuration Guide: Task-Specific Prompt Templates](configuration-guide.md#task-specific-prompt-templates) for detailed usage. ## 3. Why is LM Studio loading multiple copies of my model? This was fixed in recent versions. LEANN now properly unloads models after querying metadata, respecting your LM Studio JIT auto-evict settings. **If you still see duplicates:** - Update to the latest LEANN version - Restart LM Studio to clear loaded models - Check that you have JIT auto-evict enabled in LM Studio settings **How it works now:** 1. LEANN loads model temporarily to get context length 2. Immediately unloads after query 3. LM Studio JIT loads model on-demand for actual embeddings 4. Auto-evicts per your settings ## 4. Do I need Node.js and @lmstudio/sdk? **No, it's completely optional.** LEANN works perfectly fine without them using a built-in token limit registry. **Benefits if you install it:** - Automatic context length detection for LM Studio models - No manual registry maintenance - Always gets accurate token limits from the model itself **To install (optional):** ```bash npm install -g @lmstudio/sdk ``` See [Configuration Guide: LM Studio Auto-Detection](configuration-guide.md#lm-studio-auto-detection-optional) for details.