# brevdev/launchables

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

Repository: https://github.com/brevdev/launchables
Canonical: https://ross.abutalabs.com/products/launchables
Language: Jupyter Notebook
License: NOASSERTION
License Family: other
Last push: 2026-07-21T17:46:11+00:00

## Health v2 (maintenance only)
Score: 70/100 (v2, computed 2026-09-03T02:20:16.233290+00:00)
- activity 93, release rhythm 35, longevity 79
- inputs: {"age_days": 1115, "days_push": 43, "days_rel": null, "gap_med": null, "n_releases_24m": 0}
- flags: no_releases, no_license
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 1816, forks 314 (observed 2026-08-28T04:05:39.995283+00:00)

## What it is
A collection of Jupyter notebook guides from the Brev.dev (NVIDIA Brev) team covering LLM fine-tuning, multi-modal models, image segmentation, and other AI/ML tasks. Each notebook includes minimum GPU specs and a one-click deploy badge to run it on a GPU instance.

## Use cases
- fine-tune llama3 with direct preference optimization
- learn how to fine-tune large language models on a gpu
- run image segmentation notebooks on cloud gpus
- deploy preconfigured gpu environments for ai notebooks
- train multi-modal models with example notebooks
- find minimum gpu requirements for llm training

## When to choose
- you want hands-on, runnable notebooks for LLM fine-tuning or computer vision
- you want one-click GPU deployment instead of manual environment setup
- you are learning AI/ML tasks with guided examples

## When to avoid
- you need production training pipelines rather than tutorial notebooks
- you want a software library or API to integrate into your own code
- you need environments without GPU access

## Facets
- artifact type: learning-resource
- maturity: active
- function: machine-learning, llm-training, deep-learning, computer-vision
- domain: machine-learning, deep-learning, large-language-models, computer-vision, tutorials
- platform: python, cloud
- tags: jupyter-notebooks, fine-tuning, gpu-notebooks, nvidia-brev, one-click-deploy, multimodal-models, image-segmentation, gpu

## Member repositories
- brevdev/launchables (main) score 70

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:05:39.995283+00:00.
- Health v2: computed from the inputs above; adoption is never an input.
- Inferred fields (summary, facets, guidance): AI-extracted, prompt v1, taxonomy v1, on 2026-08-30T03:20:35.148511+00:00, confidence not recorded.
  - readme: https://github.com/brevdev/launchables (fetched 2026-08-28T04:05:39.995283+00:00, sha 3030084d9530)
- Data as of 2026-08-30T08:39:29.467469+00:00.