Name		Name	Last commit message	Last commit date
.github/ISSUE_TEMPLATE		.github/ISSUE_TEMPLATE
assets		assets
bakllava		bakllava
.gitignore		.gitignore
LAUNCHABLE-CREATION-GUIDE.md		LAUNCHABLE-CREATION-GUIDE.md
LICENSE		LICENSE
LoRAwithTensorRT-LLM.ipynb		LoRAwithTensorRT-LLM.ipynb
RAG_WIth_Local_NIM_V2.ipynb		RAG_WIth_Local_NIM_V2.ipynb
README.md		README.md
ara.ipynb		ara.ipynb
automatic1111-stable-diffusion-ui.ipynb		automatic1111-stable-diffusion-ui.ipynb
baklava.ipynb		baklava.ipynb
biomistral-finetune.ipynb		biomistral-finetune.ipynb
biomistral.ipynb		biomistral.ipynb
caltech-protein-demo.ipynb		caltech-protein-demo.ipynb
comfyui.ipynb		comfyui.ipynb
container_vulnerability_analysis.ipynb		container_vulnerability_analysis.ipynb
controlnet.ipynb		controlnet.ipynb
dbrx_inference.ipynb		dbrx_inference.ipynb
deploy-to-replicate.ipynb		deploy-to-replicate.ipynb
diffusion_lora_inference.ipynb		diffusion_lora_inference.ipynb
efficientvit-segmentation.ipynb		efficientvit-segmentation.ipynb
gemma7b.ipynb		gemma7b.ipynb
gguf-export.ipynb		gguf-export.ipynb
julia-install.ipynb		julia-install.ipynb
llama2-finetune-own-data.ipynb		llama2-finetune-own-data.ipynb
llama2-finetune.ipynb		llama2-finetune.ipynb
llama2.ipynb		llama2.ipynb
llama3-to-ollama.ipynb		llama3-to-ollama.ipynb
llama31_law.ipynb		llama31_law.ipynb
llama3_finetune_inference.ipynb		llama3_finetune_inference.ipynb
llama3dpo.ipynb		llama3dpo.ipynb
llava-finetune.ipynb		llava-finetune.ipynb
meta-chameleon-model.ipynb		meta-chameleon-model.ipynb
mistral-finetune-nemo.ipynb		mistral-finetune-nemo.ipynb
mistral-finetune-own-data.ipynb		mistral-finetune-own-data.ipynb
mistral-finetune.ipynb		mistral-finetune.ipynb
mixtral-finetune-own-data.ipynb		mixtral-finetune-own-data.ipynb
mixtral-finetune.ipynb		mixtral-finetune.ipynb
molmim-optimization.ipynb		molmim-optimization.ipynb
nemo-reranker.ipynb		nemo-reranker.ipynb
nim-quickstart.ipynb		nim-quickstart.ipynb
nvidia_nim_agents_llama3.1.ipynb		nvidia_nim_agents_llama3.1.ipynb
ocr-pdf-analysis.ipynb		ocr-pdf-analysis.ipynb
oobabooga.ipynb		oobabooga.ipynb
pdf-blueprint.ipynb		pdf-blueprint.ipynb
phi2-finetune-own-data.ipynb		phi2-finetune-own-data.ipynb
phi2-finetune.ipynb		phi2-finetune.ipynb
question_answer_nemo.ipynb		question_answer_nemo.ipynb
rapids_cudf_pandas.ipynb		rapids_cudf_pandas.ipynb
setup-k8s.ipynb		setup-k8s.ipynb
streamingllm-tensorrt.ipynb		streamingllm-tensorrt.ipynb
tensorrt-comfyui.ipynb		tensorrt-comfyui.ipynb
tensorrt-llama3.ipynb		tensorrt-llama3.ipynb
tensorrt_mistral.ipynb		tensorrt_mistral.ipynb
zephyr-chatbot.ipynb		zephyr-chatbot.ipynb

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Console • Docs • Launchables • Launchables Guide

Brev Launchables

Launchables are a feature of NVIDIA Brev that deliver preconfigured, fully optimized compute and software environments. Fast and easy to deploy, launchables allow you to start projects without extensive setup or configuration.

This repo contains helpful AI/ML notebooks for LLMs, multi-modal models, image segmentation, and more. Each notebook has been coupled with the minimum GPU specs required to use them along with a 1-click deploy badge that starts each notebook on a GPU.

Contributing

We welcome contributions to this repository! If you have a notebook you'd like to add, please open a pull request!

Notebooks

We've split the notebooks into categories based on the type of task they're designed for. Our current split is: LLM finetuning/training, multi-modal models, computer vision/image segmentation, and miscellaneous. Let us know if you want to see more notebooks for a certain task or using different frameworks and tools!

LLM Finetuning/Training

Notebook	Description	Min. GPU
Fine-tune Llama3 using Direct Preference Optimization	Fine-tune Llama3 using DPO	1x A100
Fine-tune Llama3 using SFT	Fine-tune and deploy Llama 3	2x A100
Fine-tune Llama 2	A Guide to Fine-tuning Llama 2	1x A10G
Fine-tune Llama 2 - Own Data	Fine-tune Llama 2 on your own dataset	1x A10G
Fine-tune Mistral	A Guide to Fine-tuning Mistral	1x A10G
Fine-tune Mistral using NVIDIA NeMO and PEFT	Fine-tune Mistral using NVIDIA NeMO and PEFT	1x A100
Fine-tune Mistral - Own Data	Fine-tune Mistral on your own dataset	1x A10G
Fine-tune Mixtral (8x7B MoE)	A Guide to Fine-tuning Mixtral, Mistral's 8x7B MoE	4x T4
Fine-tune Mixtral (8x7B MoE) - Own Data	A Guide to Fine-tuning Mixtral on your own dataset	4x T4
Fine-tune BioMistral	A Guide to Fine-tuning BioMistral	1x A10G
Fine-tune Phi-2	A Guide to Fine-tuning Phi-2	1x A10G
Fine-tune Phi-2 - Own Data	Fine-tune Phi-2 on your own dataset	1x A10G
Training Question/Answer models using NVIDIA NeMo	Use NeMo to train BERT, GPT, and S2S models for Q&A tasks	1x A10G

LLM Inference/Deployment

Notebook	Description	Min. GPU
Run inference on Llama3 using TensorRT-LLM	Run inference on Llama3 using TensorRT-LLM	1x A10G
Inference on DBRX with VLLM and Gradio	Run inference on DBRX with VLLM and Gradio	4x A100
Run BioMistral	Run BioMistral	1x A10G
Run Llama 2 70B	Run Llama 2 70B, or any Llama 2 Model	4x T4
Use TensorRT-LLM with Mistral	Use NVIDIA TensorRT engine to run inference on Mistral-7B	1x A10G
StreamingLLM for Optimized Inference	Use StreamingLLM for infinite length input without finetuning	1x A10G

Multi-modal and Computer Vision Models

Notebook	Description	Min. GPU
Finetune and deploy LlaVA	Finetune the LlaVA model on your own data	1x A10G
AUTOMATIC1111 Stable Diffusion WebUI	Run Stable Diffusion WebUI, AUTOMATIC1111	1x A10G
ControlNet on AUTOMATIC1111	Run ControlNet Models on Stable Diffusion WebUI	1x A10G
SDXL inference with LoRA and Diffusers	Run inference using LoRA adaptors and SDXL	1x A10G
Oobabooga LLM WebUI	Run Oobabooga, the LLM WebUI (like AUTOMATIC1111)	1x A10G
EfficientViT Segement Anything	Run a TensorRT optimized version of Segment Anything	1x A10G

Other applications and tools

Notebook	Description	Min. GPU
Deploy to Replicate	Deploy Model to Replicate	any \|\| CPU
GGUF Export FT Model	Export your fine-tuned model to GGUF	1x A10G
Julia Install	Easily Install Julia + Notebooks	any \|\| CPU
PDF Chatbot (OCR)	PDF Chatbot using OCR	1x A10G
Zephyr Chatbot	Chatbot with Open Source Models	1x A10G
Accelerate Data Science using NVIDIA RAPIDS	Accelerate Data Science using NVIDIA RAPIDS	1x A10G
Accelerate Data Science using NVIDIA RAPIDS	Accelerate Data Science using NVIDIA RAPIDS	1x A10G

What is Brev?

NVIDIA Brev provides streamlined access to NVIDIA GPU instances on popular cloud platforms, automatic environment setup, and flexible deployment options, enabling developers to start experimenting instantly.

Provision:

Brev provisions a GPU for you. You don't have to worry about setting up a cloud account. We have solid GPU supply.

Configure:

Brev configures your GPU with the right drivers and libraries. There are also advanced otpions for running docker containers or using docker compose.

Connect:

Brev CLI automatically edits your ssh config so you can ssh gpu-name or run brev open gpu-name to open VS Code, Cursor or your favorite editor to the remote machine

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Collection of notebook guides created by the Brev.dev team!

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Brev Launchables

Contributing