#fine-tuning (30 Repositories)
Ranked open-source repositories tagged with #fine-tuning, scored by pull request acceptance likelihood and maintainer engagement velocity.
57.6%
62.9h
30 repositories tagged #fine-tuning
bghira/SimpleTuner
A general fine-tuning kit geared toward image/video/audio diffusion models.
unslothai/unsloth
Local UI to run and train LLMs and diffusion models. Supports GGUF, MLX, Qwen3.8, DeepSeek-V4, MiniMax-H3, Gemma 4, FLUX and more.
kubeflow/trainer
Distributed AI Model Training and LLM Fine-Tuning on Kubernetes
dstackai/dstack
A unified orchestration layer for heterogeneous AI compute. It standardizes how to manage compute and run training and inference on GPU clouds, Kubernetes, VMs, or bare-metal clusters.
MakazhanAlpamys/Soup
Fine-tune LLMs from one YAML. Layer streaming trains an 8B model on a 4 GB laptop GPU.
beam-cloud/beta9
Ultrafast serverless GPU inference, sandboxes, and background jobs
axolotl-ai-cloud/axolotl
Go ahead and axolotl questions
huggingface/peft
🤗 PEFT: State-of-the-art Parameter-Efficient Fine-Tuning.
oumi-ai/oumi
Easily fine-tune (SFT/RL), evaluate, and deploy Qwen, Gemma, or any open agentic LLM/VLM!
Nerogar/OneTrainer
OneTrainer is a one-stop solution for all your Diffusion training needs.
X-GenGroup/Flow-Factory
A unified framework for easy fine-tuning in Flow-Matching models
Kiln-AI/Kiln
Build, Evaluate, and Optimize AI Systems. Includes evals, RAG, agents, fine-tuning, synthetic data generation, dataset management, MCP, and more.
invergent-ai/surogate
Train and serve LLMs at extreme speed and massive throughput.
AI-Hypercomputer/maxtext
A simple, performant, and scalable Jax LLM!
perfectgf/lora-dataset-studio
Self-hosted, one-tab workbench for the whole training lifecycle: build Character/Concept/Style datasets (generate, scrape, or triage a big dump in the Image Bank), curate, caption, clean watermarks, then train LoRAs on five model families or a full Krea 2 model on a rented GPU, and rank checkpoints in a Test Studio. Free & local.
Red-Hat-AI-Innovation-Team/training_hub
An algorithm-focused interface for common llm training, continual learning, and reinforcement learning techniques
hiyouga/LlamaFactory
Unified Efficient Fine-Tuning of 100+ LLMs & VLMs (ACL 2024)
h2oai/h2o-llmstudio
H2O LLM Studio - a framework and no-code GUI for fine-tuning LLMs. Documentation: https://docs.h2o.ai/h2o-llmstudio/
netease-youdao/Confucius4-TTS
Confucius4-TTS: a Multilingual and Cross-Lingual Zero-Shot TTS Engine
run-llama/llama_index
LlamaIndex is the document processing platform for AI
kubeflow/sdk
Universal Python SDK to run AI workloads on Kubernetes
RapidFireAI/rapidfireai
RapidFire AI: Rapid AI Customization from RAG to Fine-Tuning
Zyora-Dev/zse
The inference engine the open-source world built for itself.
huggingface/optimum-habana
Easy and lightning fast training of 🤗 Transformers on Habana Gaudi processor (HPU)
ai4protein/VenusFactory2
🏭 AI agent platform with skills for protein engineering, the noob-friendly AI tutorial tool for life science professionals. (ACL Demo2025, arXiv 2026)
AIDotNet/OpenDeepWiki
OpenDeepWiki is the open-source version of the DeepWiki project, aiming to provide a powerful knowledge management and collaboration platform. The project is mainly developed using C# and TypeScript, supporting modular design, and is easy to expand and customize.
pykeio/ort
Fast ML inference & training for ONNX models in Rust
calmrocks/ai-engineer-notebooks
Hands-on, framework-free Colab notebooks for the AI Engineer / Forward Deployed Engineer (FDE) skill set — model APIs, structured output, tool calling, RAG, evals-as-the-spine, agents (loop from scratch, tool design, guardrails, MCP, Skills), fine-tuning vs LoRA, prompt-injection/security, LLMOps, and customer craft. Runs on the free Groq API.
zhao-kun/VibeVoiceFusion
VibeVoiceFusion is a full-stack, multi-speaker voice generation web system featuring LoRA fine-tuning, batch generation, and VRAM optimization. Based on Microsoft's VibeVoice (AR + diffusion architecture)
modelscope/ms-cookbook
魔搭紫皮书｜ModelScope Cookbook：面向开发者的开源模型应用实战指南，覆盖模型选型、推理、微调、评测、RAG、Agent 与 AIGC，从跑通第一个模型到构建实际应用。