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Rare Earth Juejin Tech Community

Nov 24, 2023 · Artificial Intelligence

Step-by-Step Guide to Deploying LangChain‑Chatchat with ChatGLM‑2 on a Local Machine

This article provides a comprehensive tutorial on setting up the LangChain‑Chatchat open‑source project, covering environment preparation, model and embedding downloads, configuration files, database initialization, API service launch, and example curl commands for interacting with both the large language model and the local knowledge base.

APIChatGLMLangChain

0 likes · 9 min read

Step-by-Step Guide to Deploying LangChain‑Chatchat with ChatGLM‑2 on a Local Machine

JD Retail Technology

Oct 26, 2023 · Artificial Intelligence

Leveraging Large Language Models for Text-to-SQL: Prompt Design and End-to-End Pipeline

This article explains how large language models can be used to convert natural language queries into SQL statements, describes two main approaches—direct generation and fine‑tuned open‑source models—details prompt engineering techniques, and outlines an end‑to‑end pipeline that executes the generated SQL and summarizes results.

ChatGLMLLMPrompt Engineering

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Leveraging Large Language Models for Text-to-SQL: Prompt Design and End-to-End Pipeline

DaTaobao Tech

Sep 11, 2023 · Artificial Intelligence

Large Language Model Upgrade Paths and Architecture Selection

This article analyzes upgrade paths of major LLMs—ChatGLM, LLaMA, Baichuan—detailing performance, context length, and architectural changes, then examines essential capabilities, data cleaning, tokenizer and attention design, and offers practical guidance for balanced scaling and efficient model construction.

BaichuanChatGLMLLM architecture

0 likes · 32 min read

Large Language Model Upgrade Paths and Architecture Selection

DaTaobao Tech

Jul 12, 2023 · Artificial Intelligence

Optimizing ChatGLM-6B Deployment with MNN: Model Conversion, Quantization, and Edge Inference

The article details a workflow that converts the PyTorch ChatGLM‑6B model to MNN, splits and compresses embeddings, applies int4/int8 quantization, supports dynamic shapes, and uses hybrid GPU/CPU or CPU‑only loading to enable low‑memory edge inference on PCs and mobile devices with competitive token‑per‑second performance.

ChatGLMLLMMNN

0 likes · 16 min read

Optimizing ChatGLM-6B Deployment with MNN: Model Conversion, Quantization, and Edge Inference