Tools to Fine-Tune LLMs Locally
Fine-tune a language model with LoRA, QLoRA or full training on your GPUs, using Unsloth, LLaMA-Factory or TRL.
A Python package for local LLM inference and fine-tuning on Apple Silicon, built on MLX with Hugging Face model support and an MIT license.
7.2KUpdated 1 day agoMIT
macOS#Batch processing#Distributed execution#Hugging Face integration
MLX LM is an open-source Python package for generating text and fine-tuning language models locally on Apple Silicon Macs. Built on MLX, it suits developers and researchers who want to work with models through Python or a terminal, including adapting models to their own tasks. The package uses the MIT license.
Inference Libraries and BindingsLLM Fine-TuningLocal Model RunnersQuantization and Model ConversionTerminal Chat Clients+0
An open-source Python library for adapting LLMs and diffusion models with less memory and storage, under Apache 2.0.
21.7KUpdated 1 day agoApache-2.0
macOS#Distributed execution#Hugging Face integration#LoRA
PEFT is an open-source Python library for developers who want to adapt pretrained models on their own hardware with less compute and storage than full fine-tuning requires. It trains a small subset of parameters, often through adapters, while leaving the base model intact. It's licensed under Apache 2.0.
LLM Fine-TuningLoRA and Image Model TrainingTraining Frameworks+0
An open source AI platform for Kubernetes that supports self-hosted ML workflows, distributed training and model management under Apache 2.0.
15.9KUpdated 1 month agoApache-2.0
Web#MLX#Multi-user access
Kubeflow is a self-hosted AI platform for teams that run machine learning workloads on Kubernetes. It brings model development, training and production workflows into a modular stack that can run on a local laptop, on-premises infrastructure or a cloud Kubernetes cluster. It's open source under Apache 2.0.
Experiment Tracking and MLOpsKubernetes and Cloud-Native AILLM Fine-TuningTraining Frameworks+0
Apache 2.0 LLM fine-tuning framework for local or cloud GPUs, supporting NVIDIA, AMD, LoRA, QLoRA and multimodal training.
12.5KUpdated 2 days agoApache-2.0
Docker#Distributed execution#Hugging Face integration#LoRA
Axolotl is an open-source LLM fine-tuning framework for developers, researchers, and teams training models on their own data. It runs on local hardware or cloud infrastructure you control, including Docker and Kubernetes environments. The framework uses Apache 2.0, which permits commercial use.
LLM Fine-TuningQuantization and Model ConversionTraining Frameworks+0
A local AI workbench for macOS, Windows and Linux. Evaluate agents, optimize prompts and run fully offline with Ollama or use cloud APIs.
5.1KUpdated 22 hours ago
macOS · Windows · Linux#Git integration#MCP#Multi-agent workflows
Kiln is a desktop workbench for teams building AI applications on macOS, Windows and Linux. It keeps a task and its dataset together across evaluation, prompt optimization, RAG and fine-tuning, so teams can compare changes against the same examples. Engineers, data scientists, QA staff and subject matter experts can contribute through the app.
Datasets and Synthetic DataLLM Evaluation and TestingLLM Fine-TuningPrompt Management and PlaygroundsRAG Frameworks and Pipelines+0
