There are 2 repositories under supervised-finetuning topic.
InternLM-XComposer2.5-OmniLive: A Comprehensive Multimodal System for Long-term Streaming Video and Audio Interactions
This repository collects papers for "A Survey on Knowledge Distillation of Large Language Models". We break down KD into Knowledge Elicitation and Distillation Algorithms, and explore the Skill & Vertical Distillation of LLMs.
[ICLR 2025] Alignment Data Synthesis from Scratch by Prompting Aligned LLMs with Nothing. Your efficient and high-quality synthetic data generation pipeline!
Aligning Large Language Models with Human: A Survey
开源SFT数据集整理,随时补充
✨ A synthetic dataset generation framework that produces diverse coding questions and verifiable solutions - all in one framwork
The offical realization of InstructERC
[ACL 2024] The official codebase for the paper "Self-Distillation Bridges Distribution Gap in Language Model Fine-tuning".
LogLLM: Log-based Anomaly Detection Using Large Language Models (system log anomaly detection)
[ACL-25] We introduce ScaleQuest, a scalable, novel and cost-effective data synthesis method to unleash the reasoning capability of LLMs.
使用LLaMA-Factory微调多模态大语言模型的示例代码 Demo of Finetuning Multimodal LLM with LLaMA-Factory
Code for Paper (Preserving Diversity in Supervised Fine-tuning of Large Language Models)
[NeurIPS 2024 Main Track] Code for the paper titled "Instruction Tuning With Loss Over Instructions"
[NeurIPS 2025] The official repository of "Inst-IT: Boosting Multimodal Instance Understanding via Explicit Visual Prompt Instruction Tuning"
Official implementation for "Diffusion Instruction Tuning"
[AAAI 2025]Automatically Generating Numerous Context-Driven SFT Data for LLMs across Diverse Granularity
Qwen2-VL在文旅领域的LLaMA-Factory微调案例 The case for fine-tuning Qwen2-VL in the field of historical literature and museums
Finetuning Google's Gemma Model for Translating Natural Language into SQL
LLM-powered financial analyst using LoRA-tuned Llama-3 and RAG pipeline to answer complex queries over SEC 10-K filings with contextual accuracy.
Federated Fine-Tuning of LLMs on Apple Silicon with Flower.ai and MLX-LM
Python Project Sample for Demonstration
An LLM challenge to (i) fine-tune pre-trained HuggingFace transformer model to build a Code Generation language model, and (ii) build a retrieval-augmented generation (RAG) application using LangChain
Building an LLM with RLHF involves fine-tuning using human-labeled preferences. Based on Learning to Summarize from Human Feedback, it uses supervised learning, reward modeling, and PPO to improve response quality and alignment.
Various LMs/LLMs below 3B parameters (for now) trained using SFT (Supervised Fine Tuning) for several downstream tasks
Binary classification of pathological heartbeats from ECG signals using 1D CNNs in PyTorch
This project streamlines the fine-tuning process, enabling you to leverage Llama-2's capabilities for your own projects.
Federated Supervised Fine-Tuning for Small Language Models (SLMs)
[EMNLP 2025 Main] JOLT-SQL: Joint Loss Tuning of Text-to-SQL with Confusion-aware Noisy Schema Sampling
[ACL 2025 Findings] Edit Once, Update Everywhere: A Simple Framework for Cross-Lingual Knowledge Synchronization in LLMs