About Transformer Lab

This platform provides open-source tools and resources for training large language models, enabling developers and researchers to customize and deploy AI models. It facilitates collaborative development and accelerates innovation in natural language processing by offering accessible and transparent model training frameworks.

<problem> Training, evaluating, and deploying large language models (LLMs) requires complex infrastructure and specialized knowledge, creating barriers for researchers, machine learning engineers, and developers. Existing tools often lack the transparency, reproducibility, and collaborative features needed for efficient AI model development. </problem> <solution> Transformer Lab is an open-source platform designed to streamline the entire LLM lifecycle, from initial training to comprehensive evaluation and deployment. The platform enables users to collaboratively build, study, and assess AI models with built-in provenance tracking, reproducibility features, and transparency tools. It simplifies the process of fine-tuning, evaluating, exporting, and testing LLMs across various inference engines and platforms, making it easier to adapt LLMs to specific needs, whether in the cloud or on local hardware. Transformer Lab supports a wide range of hardware, including GPUs from AMD and NVIDIA, as well as Apple Silicon with MLX, and offers plugin support to extend functionality. </solution> <features> - One-click download of hundreds of popular models, including Llama3, Phi3, Mistral, Mixtral, Gemma, and Command-R, with support for downloading any LLM from Hugging Face. - Model conversion between formats such as MLX and GGUF. - Chat interface with features like completions, preset prompts, chat history, and adjustable generation parameters. - Pre-training, fine-tuning, and reinforcement learning techniques, including DPO, ORPO, SIMPO, and reward modeling. - Comprehensive evaluation tools, including Eleuther Harness, LLM-as-a-judge, objective metrics, and red-teaming evaluations, with visualization and graphing capabilities. - Plugin support for extending functionality and integrating with other tools. - RAG (Retrieval Augmented Generation) capabilities with a drag-and-drop file UI. - Cross-platform support for Windows, MacOS, and Linux, with training and inference using MLX on Apple Silicon, CUDA, and ROCm, including multi-GPU training. </features> <target_audience> Transformer Lab is primarily targeted towards researchers, machine learning engineers, and developers who need a collaborative, transparent, and reproducible platform for training, evaluating, and deploying large language models. </target_audience>

What does Transformer Lab do?

When was Transformer Lab founded?

Transformer Lab was founded in 2024.

Who founded Transformer Lab?

Transformer Lab was founded by Ali Asaria and Tony Salomone.

Ali Asaria - Co-founder
Tony Salomone - Co-founder

Founded

2024

Employees

6 employees

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Transformer Lab

Score: 93/100

AI-Generated Company Overview (experimental) – could contain errors

Executive Summary

transformerlab.ai 500+

Founded 2024

Funding

No funding information available. Click "Fetch funding" to run a targeted funding scan.

Team (5+)

Ali Asaria

Co-founder

Tony Salomone

Co-founder

Company Description

Problem

Training, evaluating, and deploying large language models (LLMs) requires complex infrastructure and specialized knowledge, creating barriers for researchers, machine learning engineers, and developers. Existing tools often lack the transparency, reproducibility, and collaborative features needed for efficient AI model development.

Solution

Transformer Lab is an open-source platform designed to streamline the entire LLM lifecycle, from initial training to comprehensive evaluation and deployment. The platform enables users to collaboratively build, study, and assess AI models with built-in provenance tracking, reproducibility features, and transparency tools. It simplifies the process of fine-tuning, evaluating, exporting, and testing LLMs across various inference engines and platforms, making it easier to adapt LLMs to specific needs, whether in the cloud or on local hardware. Transformer Lab supports a wide range of hardware, including GPUs from AMD and NVIDIA, as well as Apple Silicon with MLX, and offers plugin support to extend functionality.

Features

One-click download of hundreds of popular models, including Llama3, Phi3, Mistral, Mixtral, Gemma, and Command-R, with support for downloading any LLM from Hugging Face.

Model conversion between formats such as MLX and GGUF.

Chat interface with features like completions, preset prompts, chat history, and adjustable generation parameters.

Pre-training, fine-tuning, and reinforcement learning techniques, including DPO, ORPO, SIMPO, and reward modeling.

Comprehensive evaluation tools, including Eleuther Harness, LLM-as-a-judge, objective metrics, and red-teaming evaluations, with visualization and graphing capabilities.

Plugin support for extending functionality and integrating with other tools.

RAG (Retrieval Augmented Generation) capabilities with a drag-and-drop file UI.

Cross-platform support for Windows, MacOS, and Linux, with training and inference using MLX on Apple Silicon, CUDA, and ROCm, including multi-GPU training.

Target Audience

Transformer Lab is primarily targeted towards researchers, machine learning engineers, and developers who need a collaborative, transparent, and reproducible platform for training, evaluating, and deploying large language models.