Document Summarization API (LLM-powered)

Design and implement a Retrieval-Augmented Generation pipeline with vector database integration (Pinecone, Weaviate, or Chroma), chunking strategy, embedding model selection, and LLM integration. Includes evaluation metrics.

Comprehensive evaluation of your ML model or LLM: accuracy, latency, hallucination rate, safety benchmarks, and comparison against baseline models. Delivered as a structured PDF report with recommendations.

I'll fine-tune a small LLM (Mistral 7B, Llama 3, or similar) on your dataset (up to 50k examples). Includes data preprocessing, LoRA/QLoRA training, evaluation report, and model export in GGUF/ONNX format.