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This repo contains helpful AI/ML notebook templates 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.
We welcome contributions to this repository! If you have a notebook you'd like to add, please reach out to use the Discord or open a pull request!
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!
| Notebook | Description | Min. GPU | Deploy |
|---|---|---|---|
| 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 | |
| Notebook | Description | Min. GPU | Deploy |
|---|---|---|---|
| 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 | |
| Notebook | Description | Min. GPU | Deploy |
|---|---|---|---|
| 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 | |
| Notebook | Description | Min. GPU | Deploy |
|---|---|---|---|
| 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 | |
Brev is a dev tool that makes it really easy to code on a GPU in the cloud. Brev does 3 things: provision, configure, and connect.
Brev provisions a GPU for you. You don't have to worry about setting up a cloud account. We have solid GPU supply, but if you do have AWS or GCP, you can link them.
Brev configures your GPU with the right drivers and libraries. Use our open source tool Verb to point and click the right python and CUDA versions.
Brev.dev CLI automatically edits your ssh config so you can ssh gpu-name or run brev open gpu-name to open VS Code to the remote machine