Summary We created a guide for fine-tuning and evaluating LLMs using LangSmith for dataset management and evaluation. We did this both with an open source LLM on CoLab and HuggingFace for model training, as well as OpenAI's new finetuning service. As a test case, we fine-tuned LLaMA2-7b-chat and gpt-3.5-turbo for an extraction task (knowledge graph triple extraction) using training data exported from LangSmith and also evaluated the results using LangSmith. The CoLab guide is here. Context I
LangSaaS - No Code LangChain SaaS - Product Information, Latest Updates, and Reviews 2024
Applying OpenAI's RAG Strategies 和訳｜p
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Using LangSmith to Support Fine-tuning
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8월 2023 - 컴퓨터 vs 책
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Week of 8/21] LangChain Release Notes
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Multi-Vector Retriever for RAG on tables, text, and images 和訳｜p
