We unified the interfaces of instruction-tuning data (e.g., CoT data), multiple LLMs and parameter-efficient methods (e.g., lora, p-tuning) together for easy use. We welcome open-source enthusiasts to initiate any meaningful PR on this repo and integrate as many LLM related technologies as possible. 我们打造了方便研究人员上手和使用大模型等微调平台，我们欢迎开源爱好者发起任何有意义的pr！

• UpdatedDec 12, 2023
• Jupyter Notebook

基于ChatGLM-6B、ChatGLM2-6B、ChatGLM3-6B模型，进行下游具体任务微调，涉及Freeze、Lora、P-tuning、全参微调等

• UpdatedDec 12, 2023
• Python

An optimized deep prompt tuning strategy comparable to fine-tuning across scales and tasks

• UpdatedNov 16, 2023
• Python

A novel method to tune language models. Codes and datasets for paper ``GPT understands, too''.

• UpdatedOct 6, 2022
• Python

轻松玩转LLM兼容openai&langchain，支持文心一言、讯飞星火、腾讯混元、智谱ChatGLM等

• UpdatedSep 24, 2024
• Jupyter Notebook

Code for COLING22 paper, DPTDR: Deep Prompt Tuning for Dense Passage Retrieval

• UpdatedAug 7, 2023
• Python

Pipelines for Fine-Tuning LLMs using SFT and RLHF

• UpdatedOct 7, 2025
• Python

P-tuning-v2 integrated mrc for ner

• UpdatedMar 30, 2023
• Python

This bootcamp is designed to give NLP researchers an end-to-end overview on the fundamentals of NVIDIA NeMo framework, complete solution for building large language models. It will also have hands-on exercises complimented by tutorials, code snippets, and presentations to help researchers kick-start with NeMo LLM Service and Guardrails.

• UpdatedMar 7, 2024
• Jupyter Notebook

Comparison of different adaptation methods on PEFT for fine-tuning downstream tasks or benchmarks.

• UpdatedFeb 15, 2024
• Python

Reproduce a prompt-learning method: P-Tuning V2, from the paper 《P-Tuning v2: Prompt Tuning Can Be Comparable to Fine-tuning Universally Across Scales and Tasks》, model usage: Deberta + ChatGLM2, additional_task: RACE

• UpdatedMay 11, 2025
• Python