{"id":15031943,"url":"https://github.com/brevdev/notebooks","last_synced_at":"2025-04-11T19:45:40.019Z","repository":{"id":188538242,"uuid":"678531456","full_name":"brevdev/notebooks","owner":"brevdev","description":"Collection of notebook guides created by the Brev.dev team!","archived":false,"fork":false,"pushed_at":"2024-10-23T23:56:34.000Z","size":82878,"stargazers_count":1654,"open_issues_count":9,"forks_count":284,"subscribers_count":26,"default_branch":"main","last_synced_at":"2024-10-29T15:34:34.918Z","etag":null,"topics":[],"latest_commit_sha":null,"homepage":"","language":"Jupyter Notebook","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":"mit","status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/brevdev.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":null,"license":"LICENSE","code_of_conduct":null,"threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null,"governance":null,"roadmap":null,"authors":null,"dei":null,"publiccode":null,"codemeta":null}},"created_at":"2023-08-14T19:13:49.000Z","updated_at":"2024-10-28T19:27:04.000Z","dependencies_parsed_at":null,"dependency_job_id":"eab6a769-1c9a-482f-add7-76e9edd018e6","html_url":"https://github.com/brevdev/notebooks","commit_stats":null,"previous_names":["brevdev/notebooks"],"tags_count":0,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/brevdev%2Fnotebooks","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/brevdev%2Fnotebooks/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/brevdev%2Fnotebooks/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/brevdev%2Fnotebooks/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/brevdev","download_url":"https://codeload.github.com/brevdev/notebooks/tar.gz/refs/heads/main","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":248469134,"owners_count":21108963,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2022-07-04T15:15:14.044Z","host_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub","repositories_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories","repository_names_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repository_names","owners_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners"}},"keywords":[],"created_at":"2024-09-24T20:16:56.793Z","updated_at":"2025-04-11T19:45:39.985Z","avatar_url":"https://github.com/brevdev.png","language":"Jupyter Notebook","readme":"\u003c!-- Banner Image --\u003e\n\u003cimg src=\"https://uohmivykqgnnbiouffke.supabase.co/storage/v1/object/public/landingpage/brevdevnotebooks.png\" width=\"100%\"\u003e\n\n\u003c!-- Links --\u003e\n\u003cp align=\"center\"\u003e\n  \u003ca href=\"https://console.brev.dev\" style=\"color: #06b6d4;\"\u003eConsole\u003c/a\u003e •\n  \u003ca href=\"https://brev.dev\" style=\"color: #06b6d4;\"\u003eDocs\u003c/a\u003e •\n  \u003ca href=\"/\" style=\"color: #06b6d4;\"\u003eTemplates\u003c/a\u003e •\n  \u003ca href=\"https://discord.gg/NVDyv7TUgJ\" style=\"color: #06b6d4;\"\u003eDiscord\u003c/a\u003e\n\u003c/p\u003e\n\n# Brev.dev Notebooks\n\nThis 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.\n\n## Contributing\n\nWe welcome contributions to this repository! If you have a notebook you'd like to add, please reach out to use the [Discord](https://discord.gg/y9428NwTh3) or open a pull request!\n\n## Notebooks\n\nWe'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!\n\n### LLM Finetuning/Training\n\n| Notebook                                                                                                                       | Description                                               | Min. GPU | Deploy                                                                                                                                                                                                                                                                                                                                                                                                                                                                                |\n| ------------------------------------------------------------------------------------------------------------------------------ | --------------------------------------------------------- | -------- | ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |\n| [Fine-tune Llama3 using Direct Preference Optimization](https://github.com/brevdev/notebooks/blob/main/llama3dpo.ipynb)        | Fine-tune Llama3 using DPO                                | 1x A100  | [![Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/brevdev/notebooks/blob/main/llama3dpo.ipynb) [![ Click here to deploy.](https://brev-assets.s3.us-west-1.amazonaws.com/nv-lb-dark.svg)](https://console.brev.dev/notebook/llama3dpo)                                                                                                                                                                                    |\n| [Fine-tune Llama3 using SFT](https://github.com/brevdev/notebooks/blob/main/llama3_finetune_inference.ipynb)                   | Fine-tune and deploy Llama 3                              | 2x A100  | [![Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/brevdev/notebooks/blob/main/llama3_finetune_inference.ipynb) [![ Click here to deploy.](https://brev-assets.s3.us-west-1.amazonaws.com/nv-lb-dark.svg)](https://console.brev.dev/notebook/llama3_finetune_inference)                                                                                                                                                    |\n| [Fine-tune Llama 2](https://github.com/brevdev/notebooks/blob/main/llama2-finetune.ipynb)                                      | A Guide to Fine-tuning Llama 2                            | 1x A10G  | [![Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/brevdev/notebooks/blob/main/llama2-finetune.ipynb) [![ Click here to deploy.](https://brev-assets.s3.us-west-1.amazonaws.com/nv-lb-dark.svg)](https://console.brev.dev/notebook/llama2-finetune) [![](https://uohmivykqgnnbiouffke.supabase.co/storage/v1/object/public/landingpage/youtubebadge.svg)](https://www.youtube.com/watch?v=lPLrODJjHUE)                     |\n| [Fine-tune Llama 2 - Own Data](https://github.com/brevdev/notebooks/blob/main/llama2-finetune-own-data.ipynb)                  | Fine-tune Llama 2 on your own dataset                     | 1x A10G  | [![Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/brevdev/notebooks/blob/main/llama2-finetune-own-data.ipynb) [![ Click here to deploy.](https://brev-assets.s3.us-west-1.amazonaws.com/nv-lb-dark.svg)](https://console.brev.dev/notebook/llama2-finetune-own-data) [![](https://uohmivykqgnnbiouffke.supabase.co/storage/v1/object/public/landingpage/youtubebadge.svg)](https://www.youtube.com/watch?v=lPLrODJjHUE)   |\n| [Fine-tune Mistral](https://github.com/brevdev/notebooks/blob/main/mistral-finetune.ipynb)                                     | A Guide to Fine-tuning Mistral                            | 1x A10G  | [![Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/brevdev/notebooks/blob/main/mistral-finetune.ipynb) [![ Click here to deploy.](https://brev-assets.s3.us-west-1.amazonaws.com/nv-lb-dark.svg)](https://console.brev.dev/notebook/mistral-finetune)                                                                                                                                                                      |\n| [Fine-tune Mistral using NVIDIA NeMO and PEFT](https://github.com/brevdev/notebooks/blob/main/mistral-finetune-nemo.ipynb)     | Fine-tune Mistral using NVIDIA NeMO and PEFT              | 1x A100  | [![Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/brevdev/notebooks/blob/main/mistral-finetune-nemo.ipynb) [![ Click here to deploy.](https://brev-assets.s3.us-west-1.amazonaws.com/nv-lb-dark.svg)](https://console.brev.dev/notebook/mistral_nemo_finetune)                                                                                                                                                            |\n| [Fine-tune Mistral - Own Data](https://github.com/brevdev/notebooks/blob/main/mistral-finetune-own-data.ipynb)                 | Fine-tune Mistral on your own dataset                     | 1x A10G  | [![Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/brevdev/notebooks/blob/main/mistral-finetune-own-data.ipynb) [![ Click here to deploy.](https://brev-assets.s3.us-west-1.amazonaws.com/nv-lb-dark.svg)](https://console.brev.dev/notebook/mistral-finetune-own-data) [![](https://uohmivykqgnnbiouffke.supabase.co/storage/v1/object/public/landingpage/youtubebadge.svg)](https://www.youtube.com/watch?v=kmkcNVvEz-k) |\n| [Fine-tune Mixtral (8x7B MoE)](https://github.com/brevdev/notebooks/blob/main/mixtral-finetune.ipynb)                          | A Guide to Fine-tuning Mixtral, Mistral's 8x7B MoE        | 4x T4    | [![Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/brevdev/notebooks/blob/main/mixtral-finetune.ipynb) [![ Click here to deploy.](https://brev-assets.s3.us-west-1.amazonaws.com/nv-lb-dark.svg)](https://console.brev.dev/notebook/mixtral-finetune-own-data) [![](https://uohmivykqgnnbiouffke.supabase.co/storage/v1/object/public/landingpage/youtubebadge.svg)](https://www.youtube.com/watch?v=zbKz4g100SQ)          |\n| [Fine-tune Mixtral (8x7B MoE) - Own Data](https://github.com/brevdev/notebooks/blob/main/mixtral-finetune-own-data.ipynb)      | A Guide to Fine-tuning Mixtral on your own dataset        | 4x T4    | [![Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/brevdev/notebooks/blob/main/mixtral-finetune-own-data.ipynb) [![ Click here to deploy.](https://brev-assets.s3.us-west-1.amazonaws.com/nv-lb-dark.svg)](https://console.brev.dev/notebook/mixtral-finetune-own-data)                                                                                                                                                    |\n| [Fine-tune BioMistral](https://github.com/brevdev/notebooks/blob/main/biomistral-finetune.ipynb)                               | A Guide to Fine-tuning BioMistral                         | 1x A10G  | [![Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/brevdev/notebooks/blob/main/biomistral-finetune.ipynb) [![ Click here to deploy.](https://brev-assets.s3.us-west-1.amazonaws.com/nv-lb-dark.svg)](https://console.brev.dev/environment/new?instance=A10G:g5.xlarge\u0026name=biomistral-finetune\u0026file=https://github.com/brevdev/notebooks/raw/main/biomistral-finetune.ipynb\u0026python=3.10\u0026cuda=12.0.1)                       |\n| [Fine-tune Phi-2](https://github.com/brevdev/notebooks/blob/main/phi2-finetune.ipynb)                                          | A Guide to Fine-tuning Phi-2                              | 1x A10G  | [![Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/brevdev/notebooks/blob/main/phi2-finetune.ipynb) [![ Click here to deploy.](https://brev-assets.s3.us-west-1.amazonaws.com/nv-lb-dark.svg)](https://console.brev.dev/notebook/phi2-finetune-own-data) [![](https://uohmivykqgnnbiouffke.supabase.co/storage/v1/object/public/landingpage/youtubebadge.svg)](https://www.youtube.com/watch?v=t55XrJddjLA)                |\n| [Fine-tune Phi-2 - Own Data](https://github.com/brevdev/notebooks/blob/main/phi2-finetune-own-data.ipynb)                      | Fine-tune Phi-2 on your own dataset                       | 1x A10G  | [![Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/brevdev/notebooks/blob/main/phi2-finetune-own-data.ipynb) [![ Click here to deploy.](https://brev-assets.s3.us-west-1.amazonaws.com/nv-lb-dark.svg)](https://console.brev.dev/notebook/phi2-finetune-own-data) [![](https://uohmivykqgnnbiouffke.supabase.co/storage/v1/object/public/landingpage/youtubebadge.svg)](https://www.youtube.com/watch?v=t55XrJddjLA)       |\n| [Training Question/Answer models using NVIDIA NeMo](https://github.com/brevdev/notebooks/blob/main/question_answer_nemo.ipynb) | Use NeMo to train BERT, GPT, and S2S models for Q\u0026A tasks | 1x A10G  | [![Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/brevdev/notebooks/blob/main/question_answer_nemo.ipynb) [![ Click here to deploy.](https://brev-assets.s3.us-west-1.amazonaws.com/nv-lb-dark.svg)](https://console.brev.dev/notebook/question_answer_nemo)                                                                                                                                                              |\n\n### LLM Inference/Deployment\n\n| Notebook                                                                                                           | Description                                                   | Min. GPU | Deploy                                                                                                                                                                                                                                                                                                                                                                                                                               |\n| ------------------------------------------------------------------------------------------------------------------ | ------------------------------------------------------------- | -------- | ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------ |\n| [Run inference on Llama3 using TensorRT-LLM](https://github.com/brevdev/notebooks/blob/main/tensorrt-llama3.ipynb) | Run inference on Llama3 using TensorRT-LLM                    | 1x A10G  | [![Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/brevdev/notebooks/blob/main/tensorrt-llama3.ipynb) [![ Click here to deploy.](https://brev-assets.s3.us-west-1.amazonaws.com/nv-lb-dark.svg)](https://console.brev.dev/notebook/llama3-tensorrtllm-deployment)                                                                                                         |\n| [Inference on DBRX with VLLM and Gradio](https://github.com/brevdev/notebooks/blob/main/dbrx_inference.ipynb)      | Run inference on DBRX with VLLM and Gradio                    | 4x A100  | [![Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/brevdev/notebooks/blob/main/deploy-to-replicate.ipynb) [![ Click here to deploy.](https://brev-assets.s3.us-west-1.amazonaws.com/nv-lb-dark.svg)](https://console.brev.dev/notebooks/dbrx_inference)                                                                                                                   |\n| [Run BioMistral](https://github.com/brevdev/notebooks/blob/main/biomistral.ipynb)                                  | Run BioMistral                                                | 1x A10G  | [![Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/brevdev/notebooks/blob/main/biomistral.ipynb) [![ Click here to deploy.](https://brev-assets.s3.us-west-1.amazonaws.com/nv-lb-dark.svg)](https://console.brev.dev/environment/new?instance=A10G:g5.xlarge\u0026name=biomistral\u0026file=https://github.com/brevdev/notebooks/raw/main/biomistral.ipynb\u0026python=3.10\u0026cuda=12.0.1) |\n| [Run Llama 2 70B](https://github.com/brevdev/notebooks/blob/main/llama2-finetune-own-data.ipynb)                   | Run Llama 2 70B, or any Llama 2 Model                         | 4x T4    | [![Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/brevdev/notebooks/blob/main/llama2.ipynb) [![ Click here to deploy.](https://brev-assets.s3.us-west-1.amazonaws.com/nv-lb-dark.svg)](https://console.brev.dev/notebooks/llama2-finetune-own-data)                                                                                                                      |\n| [Use TensorRT-LLM with Mistral](https://github.com/brevdev/notebooks/blob/main/tensorrt_mistral.ipynb)             | Use NVIDIA TensorRT engine to run inference on Mistral-7B     | 1x A10G  | [![Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/brevdev/notebooks/blob/main/tensorrt_mistral.ipynb) [![ Click here to deploy.](https://brev-assets.s3.us-west-1.amazonaws.com/nv-lb-dark.svg)](https://console.brev.dev/notebook/trtmistral1)                                                                                                                          |\n| [StreamingLLM for Optimized Inference](https://github.com/brevdev/notebooks/blob/main/streamingllm-tensorrt.ipynb) | Use StreamingLLM for infinite length input without finetuning | 1x A10G  | [![Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/brevdev/notebooks/blob/main/streamingllm-tensorrt.ipynb) [![ Click here to deploy.](https://brev-assets.s3.us-west-1.amazonaws.com/nv-lb-dark.svg)](https://console.brev.dev/notebook/streamingllm-tensorrt-llm)                                                                                                       |\n\n### Multi-modal and Computer Vision Models\n\n| Notebook                                                                                                                       | Description                                          | Min. GPU | Deploy                                                                                                                                                                                                                                                                                                                                                                                                                                                                                  |\n| ------------------------------------------------------------------------------------------------------------------------------ | ---------------------------------------------------- | -------- | --------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |\n| [Finetune and deploy LlaVA](https://github.com/brevdev/notebooks/blob/main/llava-finetune.ipynb)                               | Finetune the LlaVA model on your own data            | 1x A10G  | [![Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/brevdev/notebooks/blob/main/llava-finetune.ipynb) [![ Click here to deploy.](https://brev-assets.s3.us-west-1.amazonaws.com/nv-lb-dark.svg)](https://console.brev.dev/notebook/llava-finetune) [![](https://uohmivykqgnnbiouffke.supabase.co/storage/v1/object/public/landingpage/youtubebadge.svg)](https://www.youtube.com/watch?v=XICHJx2_Rm8)                         |\n| [AUTOMATIC1111 Stable Diffusion WebUI](https://github.com/brevdev/notebooks/blob/main/automatic1111-stable-diffusion-ui.ipynb) | Run Stable Diffusion WebUI, AUTOMATIC1111            | 1x A10G  | [![Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/brevdev/notebooks/blob/main/stable-diffusion-ui.ipynb) [![ Click here to deploy.](https://brev-assets.s3.us-west-1.amazonaws.com/nv-lb-dark.svg)](https://console.brev.dev/notebook/automatic1111-stable-diffusion-ui) [![](https://uohmivykqgnnbiouffke.supabase.co/storage/v1/object/public/landingpage/youtubebadge.svg)](https://www.youtube.com/watch?v=Sf6PwCz6fbI) |\n| [ControlNet on AUTOMATIC1111](https://github.com/brevdev/notebooks/blob/main/controlnet.ipynb)                                 | Run ControlNet Models on Stable Diffusion WebUI      | 1x A10G  | [![Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/brevdev/notebooks/blob/main/controlnet.ipynb) [![ Click here to deploy.](https://brev-assets.s3.us-west-1.amazonaws.com/nv-lb-dark.svg)](https://console.brev.dev/notebook/controlnet)                                                                                                                                                                                    |\n| [SDXL inference with LoRA and Diffusers](https://github.com/brevdev/notebooks/blob/main/diffusion_lora_inference.ipynb)        | Run inference using LoRA adaptors and SDXL           | 1x A10G  | [![Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/brevdev/notebooks/blob/main/diffusion_lora_inference.ipynb) [![ Click here to deploy.](https://brev-assets.s3.us-west-1.amazonaws.com/nv-lb-dark.svg)](https://console.brev.dev/notebook/diffusion_lora_inf)                                                                                                                                                              |\n| [Oobabooga LLM WebUI](https://github.com/brevdev/notebooks/blob/main/oobabooga.ipynb)                                          | Run Oobabooga, the LLM WebUI (like AUTOMATIC1111)    | 1x A10G  | [![Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/brevdev/notebooks/blob/main/oobabooga.ipynb) [![ Click here to deploy.](https://brev-assets.s3.us-west-1.amazonaws.com/nv-lb-dark.svg)](https://console.brev.dev/notebook/oobabooga)                                                                                                                                                                                      |\n| [EfficientViT Segement Anything](https://github.com/brevdev/notebooks/blob/main/efficientvit-segmentation.ipynb)               | Run a TensorRT optimized version of Segment Anything | 1x A10G  | [![Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/brevdev/notebooks/blob/main/efficientvit-segmentation.ipynb) [![ Click here to deploy.](https://brev-assets.s3.us-west-1.amazonaws.com/nv-lb-dark.svg)](https://console.brev.dev/notebook/efficientvit-segmentation)                                                                                                                                                      |\n\n### Other applications and tools\n\n| Notebook                                                                                                               | Description                                 | Min. GPU     | Deploy                                                                                                                                                                                                                                                                                                                                                                                                                                                                    |\n| ---------------------------------------------------------------------------------------------------------------------- | ------------------------------------------- | ------------ | ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |\n| [Deploy to Replicate](https://github.com/brevdev/notebooks/blob/main/deploy-to-replicate.ipynb)                        | Deploy Model to Replicate                   | any \\|\\| CPU | [![Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/brevdev/notebooks/blob/main/deploy-to-replicate.ipynb) [![ Click here to deploy.](https://brev-assets.s3.us-west-1.amazonaws.com/nv-lb-dark.svg)](https://console.brev.dev/notebook/deploy-to-replicate) [![](https://uohmivykqgnnbiouffke.supabase.co/storage/v1/object/public/landingpage/youtubebadge.svg)](https://www.youtube.com/watch?v=eczHFcqx1ic) |\n| [GGUF Export FT Model](https://github.com/brevdev/notebooks/blob/main/gguf-export.ipynb)                               | Export your fine-tuned model to GGUF        | 1x A10G      | [![Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/brevdev/notebooks/blob/main/gguf-export.ipynb) [![ Click here to deploy.](https://brev-assets.s3.us-west-1.amazonaws.com/nv-lb-dark.svg)](https://console.brev.dev/notebook/gguf-export)                                                                                                                                                                    |\n| [Julia Install](https://github.com/brevdev/notebooks/blob/main/julia-install.ipynb)                                    | Easily Install Julia + Notebooks            | any \\|\\| CPU | [![Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/brevdev/notebooks/blob/main/julia-install.ipynb) [![ Click here to deploy.](https://brev-assets.s3.us-west-1.amazonaws.com/nv-lb-dark.svg)](https://console.brev.dev/notebook/julia-install)                                                                                                                                                                |\n| [PDF Chatbot (OCR)](https://github.com/brevdev/notebooks/blob/main/ocr-pdf-analysis.ipynb)                             | PDF Chatbot using OCR                       | 1x A10G      | [![Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/brevdev/notebooks/blob/main/ocr-pdf-analysis.ipynb) [![ Click here to deploy.](https://brev-assets.s3.us-west-1.amazonaws.com/nv-lb-dark.svg)](https://console.brev.dev/notebooks/ocr-pdf-analysis)                                                                                                                                                         |\n| [Zephyr Chatbot](https://github.com/brevdev/notebooks/blob/main/zephyr-chatbot.ipynb)                                  | Chatbot with Open Source Models             | 1x A10G      | [![Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/brevdev/notebooks/blob/main/zephyr-chatbot.ipynb) [![ Click here to deploy.](https://brev-assets.s3.us-west-1.amazonaws.com/nv-lb-dark.svg)](https://console.brev.dev/notebook/zephyr-chatbot)                                                                                                                                                              |\n| [Accelerate Data Science using NVIDIA RAPIDS](https://github.com/brevdev/notebooks/blob/main/rapids_cudf_pandas.ipynb) | Accelerate Data Science using NVIDIA RAPIDS | 1x A10G      | [![Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/brevdev/notebooks/blob/main/rapids_cudf_pandas.ipynb) [![ Click here to deploy.](https://brev-assets.s3.us-west-1.amazonaws.com/nv-lb-dark.svg)](https://console.brev.dev/notebook/rapids_cudf_pandas)                                                                                                                                                      |\n| [Accelerate Data Science using NVIDIA RAPIDS](https://github.com/brevdev/notebooks/blob/main/rapids_cudf_pandas.ipynb) | Accelerate Data Science using NVIDIA RAPIDS | 1x A10G      | [![Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/brevdev/notebooks/blob/main/rapids_cudf_pandas.ipynb) [![ Click here to deploy.](https://brev-assets.s3.us-west-1.amazonaws.com/nv-lb-dark.svg)](https://console.brev.dev/notebook/rapids_cudf_pandas) [![ Click here to deploy.](https://brev-assets.s3.us-west-1.amazonaws.com/nv-lb-light.svg)](https://console.brev.dev/notebook/rapids_cudf_pandas)    |\n\n---\n\n### What is Brev.dev?\n\nBrev 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.\n\n#### Provision:\n\nBrev 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.\n\n#### Configure:\n\nBrev 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.\n\n#### Connect:\n\nBrev.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\n","funding_links":[],"categories":[],"sub_categories":[],"project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fbrevdev%2Fnotebooks","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fbrevdev%2Fnotebooks","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fbrevdev%2Fnotebooks/lists"}