The open source research environment for AI researchers to seamlessly train, evaluate, and scale models from local hardware to GPU clusters.
5,186
stars
11,342
commits
Python
primary language
Sep 9, 2026
updated
README
The Operating System for AI Research Labs
Designed for ML Researchers. Local, on-prem, or in the cloud. Open source.
⬇️ Install for Individuals · 🏢 Install for Teams · 📖 Documentation · 🎬 Demo · 💬 Discord
✨ What is Transformer Lab?
Transformer Lab is an open-source machine learning platform that unifies the fragmented AI tooling landscape into a single, elegant interface. It is available in two editions:
👤 For IndividualsPerfect for researchers and hobbyists working on a single machine.
|
🏢 For TeamsBuilt for research labs scaling across GPU clusters.
|
🛠️ Key Capabilities
🧠 Foundation Models & LLMs
- Universal Support: Download and run Llama 3, DeepSeek, Mistral, Qwen, Phi, and more.
- Inference Engines: Support for MLX, vLLM, Ollama, and HuggingFace Transformers.
- Format Conversion: Seamlessly convert between HuggingFace, GGUF, and MLX formats.
- Chat Interface: Multi-turn chat, batched querying, and function calling support.
🎓 Training & Fine-tuning
- Unified Interface: Train on local hardware or submit tasks to remote clusters using the same UI.
- Methods: Full fine-tuning, LoRA/QLoRA, RLHF (DPO, ORPO, SIMPO), and Reward Modeling.
- Hardware Agnostic: Optimized trainers for Apple Silicon (MLX), NVIDIA (CUDA), and AMD (ROCm).
- Hyperparameter Sweeps: Define parameter ranges in YAML and automatically schedule grid searches.
🎨 Diffusion & Image Generation
- Generation: Text-to-Image, Image-to-Image, and Inpainting using Stable Diffusion and Flux.
- Advanced Control: Full support for ControlNets and IP-Adapters.
- Training: Train custom LoRA adaptors on your own image datasets.
- Dataset Management: Auto-caption images using WD14 taggers.
📊 Evaluation & Analytics
- LLM-as-a-Judge: Use local or remote models to score outputs on bias, toxicity, and faithfulness.
- Benchmarks: Built-in support for EleutherAI LM Evaluation Harness (MMLU, HellaSwag, GSM8K, etc.).
- Red Teaming: Automated vulnerability testing for PII leakage, prompt injection, and safety.
🔌 Plugins & Extensibility
- Plugin System: Extend functionality with a robust Python plugin architecture.
- Lab SDK: Integrate your existing Python training scripts (
import lab) to get automatic logging, progress bars, and artifact tracking. - CLI: Power-user command line tool for submitting tasks and monitoring jobs without a browser.
🗣️ Audio Generation
- Text-to-Speech: Generate speech using Kokoro, Bark, and other state-of-the-art models.
- Training: Fine-tune TTS models on custom voice datasets.
📥 Quick Start
1. Install
curl https://lab.cloud/install.sh | bash
2. Run
cd ~/.transformerlab/src
./run.sh
3. Access
Open your browser to http://localhost:8338.
Requirements
| Platform | Requirements |
|---|---|
| macOS | Apple Silicon (M1/M2/M3/M4) |
| Linux | NVIDIA or AMD GPU |
| Windows | NVIDIA GPU via WSL2 (setup guide) |
🏢 Enterprise & Cluster Setup
Transformer Lab for Teams runs as an overlay on your existing infrastructure. It does not replace your scheduler; it acts as a modern control plane for it.
To configure Transformer Lab to talk to Slurm or SkyPilot:
- Follow the Teams Install Guide.
- Configure your compute providers in the Team Settings.
- Use the CLI (
lab) or Web UI to queue tasks across your cluster.
👩💻 Development
Frontend
# Requires Node.js v22
npm install
npm start
Backend (API)
cd api
./install.sh # Sets up Conda env + Python deps
./run.sh # Start the API server
Lab SDK
pip install transformerlab
🤝 Contributing
We are an open-source initiative backed by builders who care about the future of AI research. We welcome contributions! Please check our issues for open tasks.
📄 License
AGPL-3.0 · See LICENSE for details.
📚 Citation
@software{transformerlab,
author = {Asaria, Ali and Salomone, Tony},
title = {Transformer Lab: The Operating System for AI Research},
year = 2023,
url = {https://github.com/transformerlab/transformerlab-app}
}
💬 Community
Built with ❤️ by Transformer Lab in Canada 🇨🇦
Contributors
Similar repos
Languages
Python
71.0%
TypeScript
26.9%
Shell
1.3%
The open source research environment for AI researchers to seamlessly train, evaluate, and scale models from local hardware to GPU clusters.
5,186
stars
11,342
commits
Python
primary language
Sep 9, 2026
updated
README
The Operating System for AI Research Labs
Designed for ML Researchers. Local, on-prem, or in the cloud. Open source.
⬇️ Install for Individuals · 🏢 Install for Teams · 📖 Documentation · 🎬 Demo · 💬 Discord
✨ What is Transformer Lab?
Transformer Lab is an open-source machine learning platform that unifies the fragmented AI tooling landscape into a single, elegant interface. It is available in two editions:
👤 For IndividualsPerfect for researchers and hobbyists working on a single machine.
|
🏢 For TeamsBuilt for research labs scaling across GPU clusters.
|
🛠️ Key Capabilities
🧠 Foundation Models & LLMs
- Universal Support: Download and run Llama 3, DeepSeek, Mistral, Qwen, Phi, and more.
- Inference Engines: Support for MLX, vLLM, Ollama, and HuggingFace Transformers.
- Format Conversion: Seamlessly convert between HuggingFace, GGUF, and MLX formats.
- Chat Interface: Multi-turn chat, batched querying, and function calling support.
🎓 Training & Fine-tuning
- Unified Interface: Train on local hardware or submit tasks to remote clusters using the same UI.
- Methods: Full fine-tuning, LoRA/QLoRA, RLHF (DPO, ORPO, SIMPO), and Reward Modeling.
- Hardware Agnostic: Optimized trainers for Apple Silicon (MLX), NVIDIA (CUDA), and AMD (ROCm).
- Hyperparameter Sweeps: Define parameter ranges in YAML and automatically schedule grid searches.
🎨 Diffusion & Image Generation
- Generation: Text-to-Image, Image-to-Image, and Inpainting using Stable Diffusion and Flux.
- Advanced Control: Full support for ControlNets and IP-Adapters.
- Training: Train custom LoRA adaptors on your own image datasets.
- Dataset Management: Auto-caption images using WD14 taggers.
📊 Evaluation & Analytics
- LLM-as-a-Judge: Use local or remote models to score outputs on bias, toxicity, and faithfulness.
- Benchmarks: Built-in support for EleutherAI LM Evaluation Harness (MMLU, HellaSwag, GSM8K, etc.).
- Red Teaming: Automated vulnerability testing for PII leakage, prompt injection, and safety.
🔌 Plugins & Extensibility
- Plugin System: Extend functionality with a robust Python plugin architecture.
- Lab SDK: Integrate your existing Python training scripts (
import lab) to get automatic logging, progress bars, and artifact tracking. - CLI: Power-user command line tool for submitting tasks and monitoring jobs without a browser.
🗣️ Audio Generation
- Text-to-Speech: Generate speech using Kokoro, Bark, and other state-of-the-art models.
- Training: Fine-tune TTS models on custom voice datasets.
📥 Quick Start
1. Install
curl https://lab.cloud/install.sh | bash
2. Run
cd ~/.transformerlab/src
./run.sh
3. Access
Open your browser to http://localhost:8338.
Requirements
| Platform | Requirements |
|---|---|
| macOS | Apple Silicon (M1/M2/M3/M4) |
| Linux | NVIDIA or AMD GPU |
| Windows | NVIDIA GPU via WSL2 (setup guide) |
🏢 Enterprise & Cluster Setup
Transformer Lab for Teams runs as an overlay on your existing infrastructure. It does not replace your scheduler; it acts as a modern control plane for it.
To configure Transformer Lab to talk to Slurm or SkyPilot:
- Follow the Teams Install Guide.
- Configure your compute providers in the Team Settings.
- Use the CLI (
lab) or Web UI to queue tasks across your cluster.
👩💻 Development
Frontend
# Requires Node.js v22
npm install
npm start
Backend (API)
cd api
./install.sh # Sets up Conda env + Python deps
./run.sh # Start the API server
Lab SDK
pip install transformerlab
🤝 Contributing
We are an open-source initiative backed by builders who care about the future of AI research. We welcome contributions! Please check our issues for open tasks.
📄 License
AGPL-3.0 · See LICENSE for details.
📚 Citation
@software{transformerlab,
author = {Asaria, Ali and Salomone, Tony},
title = {Transformer Lab: The Operating System for AI Research},
year = 2023,
url = {https://github.com/transformerlab/transformerlab-app}
}
💬 Community
Built with ❤️ by Transformer Lab in Canada 🇨🇦
Similar repos
Contributors
Languages
Python
71.0%
TypeScript
26.9%
Shell
1.3%