Turn ideas into AI, Lightning fast. Creators of PyTorch Lightning, Lightning AI Studio, TorchMetrics, Fabric, Lit-GPT, Lit-LLaMA
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Lightning-AI has a significant public presence on GitHub, showcasing a wide range of repositories primarily in Python, Jupyter Notebook, and TypeScript. Notable projects include PyTorch Lightning, a framework for AI model training, and Lit-GPT, which supports high-performance language model deployment. These repositories reflect the organization's commitment to advancing AI technologies.
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Public repositories
pytorch-lightning
Pretrain, finetune ANY AI model of ANY size on 1 or 10,000+ GPUs with zero code changes.
litgpt
20+ high-performance LLMs with recipes to pretrain, finetune and deploy at scale.
lit-llama
Implementation of the LLaMA language model based on nanoGPT. Supports flash attention, Int8 and GPTQ 4bit quantization, LoRA and LLaMA-Adapter fine-tuning, pre-training. Apache 2.0-licensed.
LitServe
A minimal Python framework for building custom AI inference servers with full control over logic, batching, and scaling.
torchmetrics
Machine learning metrics for distributed, scalable PyTorch applications.
lightning-thunder
PyTorch compiler that accelerates training and inference. Get built-in optimizations for performance, memory, parallelism, and easily write your own.
deep-learning-project-template
Pytorch Lightning code guideline for conferences
litData
Speed up model training by fixing data loading.
dl-fundamentals
Deep Learning Fundamentals -- Code material and exercises
tutorials
Collection of Pytorch lightning tutorial form as rich scripts automatically transformed to ipython notebooks.
engineering-class
Lightning Bits: Engineering for Researchers repo
forked-pdb
Python pdb for multiple processes
utilities
Common Python utilities and GitHub Actions in Lightning Ecosystem
litAI
LLM router + minimal agent framework in one. Call any LLM API with OpenAI format. Unified billing, tools, retries, fallback, logging. Build agents and AI apps in pure Python. Full control. Zero magic.
ecosystem-ci
Automate issue discovery for your projects against Lightning nightly and releases.
LitModels
Save, load, host, and share AI model checkpoints without slowing down training. Host on Lightning AI or your own cloud with enterprise-grade access controls.
LitLogger
A minimal Python logger that tracks everything you try when building AI - metrics, prompts, models, etc, so you can see what changed and why.
lightning-Habana
Lightning support for Intel Habana accelerators.
probot
No description provided for this repository.
lightning-Graphcore
No description provided for this repository.
Lightning-multinode-templates
Multinode templates for Pytorch Lightning
hello-studio
Starter projects for Lightning Studios
litperf
Lightweight performance tracker for Python code - zero overhead when disabled.
lm-evaluation-harness
A framework for few-shot evaluation of autoregressive language models.
skypilot
Run, manage, and scale AI workloads on any AI infrastructure. Use one system to access & manage all AI compute (Kubernetes, Slurm, 20+ clouds, on-prem).
.github
No description provided for this repository.
Frequently asked questions
What does Lightning-AI build on GitHub?
Lightning-AI builds a variety of tools and frameworks on GitHub, including PyTorch Lightning for model training and Lit-GPT for deploying language models. Their repositories focus on facilitating AI development and enhancing performance across different applications.
Which programming languages does Lightning-AI use?
Lightning-AI primarily uses Python for its development work, alongside Jupyter Notebook for educational content and TypeScript for specific projects. This diverse language usage supports their wide-ranging AI-focused repositories.
Are Lightning-AI's repositories public?
Yes, all of Lightning-AI's repositories are public on GitHub. This openness allows the community to access, contribute to, and utilize their various AI tools and frameworks, fostering collaboration and innovation in the field.
Is this exposure intended?
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