This repository provides a curated collection of AI/ML notebook templates focused on LLMs, multi-modal models, and computer vision tasks. It targets developers and researchers seeking practical, runnable examples with clear GPU requirements and one-click deployment options, simplifying the setup and execution of complex AI models.

How It Works

The project offers pre-configured Jupyter notebooks, each accompanied by minimum required GPU specifications and a "deploy" badge. This badge integrates with the Brev.dev platform, enabling one-click provisioning and configuration of cloud GPU instances, abstracting away the complexities of environment setup and cloud infrastructure management.

Quick Start & Requirements

• Install/Run: No direct installation; notebooks are designed to be launched via Brev.dev's one-click deploy badges.
• Prerequisites: GPU instances (specific types like A100, A10G, T4 are listed per notebook), cloud provider account (optional, can use Brev's provisioning).
• Setup: Minimal, as Brev.dev handles provisioning and configuration.
• Links: Console, Docs, Templates, Discord

Highlighted Details

• Comprehensive coverage of LLM fine-tuning (Llama3, Llama 2, Mistral, Mixtral) and inference (TensorRT-LLM, VLLM).
• Includes multi-modal and computer vision examples like LlaVA, Stable Diffusion WebUI, and ControlNet.
• Features notebooks for accelerating data science with NVIDIA RAPIDS and exporting models to GGUF.
• Provides guidance on deploying models to platforms like Replicate.

Maintenance & Community

• Maintained by the Brev.dev team.
• Actively welcomes contributions via pull requests or Discord.
• Community support available via Discord.

Licensing & Compatibility

• The repository itself appears to be under an unspecified license, but the notebooks likely rely on various underlying libraries with their own licenses. Brev.dev's service terms would apply for deployment.

Limitations & Caveats

• The "one-click deploy" functionality is tied to the Brev.dev platform, which may have associated costs or usage limitations.
• GPU requirements are explicitly stated, meaning users without access to specific GPU hardware will be unable to run certain notebooks.