Litgpt

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LitGPT is an open-source coding & development tool that provides 20+ high-performance LLMs with recipes to pretrain, finetune, and deploy at scale. It offers from-scratch implementations with no abstractions for optimized performance.

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At a glance

Pricing

Open Source

Free tier

Yes

API

Yes

Skill level

Technical

About

What is litgpt?

LitGPT is a comprehensive open-source toolkit designed for developers and AI researchers working with large language models. It offers over 20 high-performance LLMs, each implemented from scratch without abstractions, ensuring full control and optimized performance. The platform provides ready-to-use recipes for pretraining, finetuning, and deploying these models at scale, supporting features like Flash Attention, FSDP, LoRA, QLoRA, and Adapter finetuning. LitGPT is built to reduce GPU memory usage through various precision settings (FP16, BF16) and quantization techniques (4-bit, 8-bit). It supports deployment as inference APIs and offers command-line interfaces for advanced workflows, making it suitable for enterprise-level applications and academic research.

Best used for

Ideal for developers and data scientists who need to customize existing LLMs, deploy them as inference APIs, and optimize their performance for specific applications. Especially valuable for those requiring full control over model implementations and seeking to reduce computational costs.

Common actions

pretrain LLMs

finetune LLMs

deploy LLMs

optimize LLMs

evaluate LLMs

"AI Agents"face swappingautomated workflowdeepfakecollaborationgithub copilotlow-code/no-codeworkflowsopen-source

Capabilities

Key features

20+ LLM implementations
Pretrain, finetune, deploy
Flash Attention v2
FSDP multi-GPU support
LoRA, QLoRA, Adapter
Reduce GPU memory
Quantization support

Target Audience

developerdata scientiststartup founder

Integrations

Not yet documented

Pricing & Plans

Open Source

Free

FAQs

What types of LLMs are available in LitGPT?

LitGPT includes over 20 high-performance LLMs, such as Llama 3, Code Llama, Gemma, Phi, Qwen, and Mistral. Each model is implemented from scratch to maximize performance and remove layers of abstraction, providing developers with full control over their chosen architecture.

Can I use LitGPT to finetune models on my own custom datasets?

Yes, LitGPT supports finetuning LLMs on custom datasets. You can provide your own JSON or text files, and the tool offers various parameter-efficient finetuning methods like LoRA, QLoRA, and Adapter to specialize models for your specific tasks.

How does LitGPT help reduce GPU memory requirements?

LitGPT incorporates several features to lower memory requirements, including low-precision settings like FP16 and BF16, as well as quantization techniques such as 4-bit floats, 8-bit integers, and double quantization. This allows models to run efficiently on lower-memory GPUs.

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