LibreAI / Vídeo / Jellyfish
// video · Forget-C/Jellyfish

Jellyfish

Jellyfish es un proyecto de vídeo de código abierto de Forget-C (Forget-C/Jellyfish en GitHub). Tiene 6.599 estrellas en GitHub y 1.134 bifurcaciones, se publica bajo la licencia Apache-2.0 y se actualizó por última vez en GitHub el 30 de julio de 2026.

An end-to-end production workspace for AI-generated short dramas. From script input to structured storyboarding, consistency management,…

★ 6,6k estrellas⑂ 1,1k bifurcacionesApache-2.0actualizado jul 2026
▦ visual: el README de este proyecto no incluye ninguna captura incrustable,
así que aquí va un marcador. La guía de abajo está completa de todos modos.
// datos del proyecto

Datos del proyecto

Estrellas en GitHub
6.599
Bifurcaciones
1.134
Licencia
Apache-2.0
Última actualización en GitHub
30 de julio de 2026
Categoría
Vídeo
Tipo de ficha
Guía de instalación completa
Sitio oficial
Official site
// cómo funciona

Cómo funciona

  1. Pick your task

    Generation, restoration, upscaling, face swap, or lip sync — each project here specializes, so start from the job to be done.

  2. Get the weights

    Download the model files the project needs; most READMEs link exact versions and where to place them.

  3. Set up the environment

    Python environments or Docker images are the norm — follow the install section for your GPU.

  4. Run and iterate

    Feed in prompts or source media, tune the settings, and re-run until the result lands.

// características

Por qué gusta tanto

Open weights

Real model files you download and run — no API key, no per-second billing.

Local inference

Everything happens on your machine; footage never uploads anywhere.

Specialized pipelines

Each tool focuses on one job and does it well, instead of a shallow all-in-one.

Active research roots

Many of these ship alongside papers and keep absorbing new techniques.

Community workflows

Shared settings, presets, and integrations (especially around ComfyUI) multiply what one tool can do.

Commercial-friendly options

Several use permissive licenses — always confirm the model license for your use case.

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// ejecútalo

Ejecútalo tú mismo

  1. Step 1 — Clone the repo

    Download the source and move into the project folder.

    git clone https://github.com/Forget-C/Jellyfish.git
    cd Jellyfish
  2. Step 2 — Create an environment

    Isolate dependencies so nothing clashes with your other projects.

    python -m venv .venv
    source .venv/bin/activate  # Windows: .venv\Scripts\activate
  3. Step 3 — Install and launch

    Install the requirements, then follow the README's launch command (it varies per project).

    pip install -r requirements.txt
// casos de uso

Qué puedes crear

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// preguntas frecuentes

Preguntas frecuentes

What GPU do I need?

It varies widely — upscalers run on modest cards, while full video diffusion wants serious VRAM. Check each project's docs.

Are the outputs commercially usable?

Often yes for the code, but model weights carry their own licenses — read both.

Who maintains Jellyfish?

It is an open-source project at Forget-C/Jellyfish with 1,134 forks. Check the repo's contributors and recent commits to see how active maintenance is.

How is quality vs commercial tools?

The gap keeps shrinking; for restoration and upscaling, open tools already match or beat paid ones.

Do these run on Mac?

Some do via MPS or CPU, but NVIDIA on Linux/Windows is the best-supported path.

Where do I get help?

GitHub issues and Discussions on each repo, plus Discord communities for the popular ones.

// sigue explorando

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// alternativas

Alternativas en Vídeo

Los demás proyectos de Vídeo con más estrellas del catálogo de LibreAI: la lista realista de alternativas si Jellyfish no es lo que buscas.

// más en video

Más en Vídeo

Proyectos de Vídeo cercanos en el catálogo, los más próximos en estrellas a Jellyfish: sigue explorando a ambos lados.

Consigue Jellyfish

Gratis y abierto: consigue el código fuente, dale una estrella al repositorio y empieza a crear.