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ComfyUI NetflixVoid

This repository provides the pq5 quantized release of Void for use with ComfyUI-NetflixVoid.

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Art
UNet
Dateigröße
411 MB–10,4 GB
Version
vRevision 49e4c61
Aktualisiert
3. Nov. 2026
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0
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Quelle
Hugging Face

Quellenbeschreibung

NetflixVoid PQ5 for ComfyUI-NetflixVoid

This repository provides the pq5 quantized release of Void for use with ComfyUI-NetflixVoid.

Node implementation: https://github.com/jaskirat05/ComfyUI-NetflixVoid

Overview

This model package is intended for users running the Void workflow through the ComfyUI-NetflixVoid node implementation. It includes the quantized transformer checkpoints and is designed for local inference on supported hardware.

Requirements

  • Minimum VRAM: 16 GB

Installation

Place the model files into the corresponding ComfyUI directories shown below.

Transformer

Copy the transformer checkpoint files from the transformer/ folder in this Hugging Face repository to:

models/checkpoints/

Files:

  • void_pass1.safetensors
  • void_pass2.safetensors

Text Encoder

Copy the text encoder files to:

models/text_encoders/void/

Files:

  • config.json
  • model-00001-of-00002.safetensors
  • model-00002-of-00002.safetensors
  • model.safetensors.index.json

VAE

Copy the VAE files to:

models/vae/

File:

  • diffusion_pytorch_model.safetensors

VLM Dependency

This setup uses Gemma 4 for VLM-based analysis. The dependency is downloaded automatically by the node implementation, so no manual installation is required for that component.

Example Workflow

Example workflows are available in the examples directory of the ComfyUI-NetflixVoid repository:

https://github.com/jaskirat05/ComfyUI-NetflixVoid/tree/main/examples

Related Repository

Main implementation repository:

https://github.com/jaskirat05/ComfyUI-NetflixVoid

Credits

PQ5 quantization credit goes to caiovicentino1 for the related Hugging Face release:

https://huggingface.co/caiovicentino1/VOID-Netflix-HLWQ-Q5

Expected Directory Structure

After downloading and placing all required files in the correct locations, your ComfyUI directory should look similar to this:

ComfyUI/
├── models/
│   ├── checkpoints/
│   │   ├── void_pass1.safetensors
│   │   └── void_pass2.safetensors
│   ├── text_encoders/
│   │   └── void/
│   │       ├── config.json
│   │       ├── model-00001-of-00002.safetensors
│   │       ├── model-00002-of-00002.safetensors
│   │       └── model.safetensors.index.json
│   └── vae/
│       └── diffusion_pytorch_model.safetensors
└── custom_nodes/
    └── ComfyUI-NetflixVoid/

Quellen

1 Quelle
Hugging FacePrimärVersion 49e4c61f969cd23060c6fe7463ea5408c02b6ae0
huggingface.co/jaski055/ComfyUI-NetflixVoid/tree/49e4c61f969cd23060c6fe7463ea5408c02b6ae0

Verifiziert 2. Okt.

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Modellartefakte

5 Artefakte

text_encoder/model-00001-of-00002.safetensors

safetensors · 4,65 GB · SHA-256 7a9b3927bb86…9922 · Hugging Face

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text_encoder/model-00002-of-00002.safetensors

safetensors · 4,22 GB · SHA-256 4c426ef236c0…4f74 · Hugging Face

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transformer/void_pass1.safetensors

safetensors · 10,4 GB · SHA-256 51434ba83a93…4640 · Hugging Face

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transformer/void_pass2.safetensors

safetensors · 10,4 GB · SHA-256 3c986f31c88e…a82a · Hugging Face

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vae/diffusion_pytorch_model.safetensors

safetensors · 411 MB · SHA-256 bd47d57ad948…2024 · Hugging Face

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Quellenauszüge

2 Auszüge

--- license: other tags: - comfyui - image-generation - quantized-model - void - netflixvoid - pq5 library_name: diffusers --- # NetflixVoid PQ5 for ComfyUI-NetflixVoid This repository provides the `pq5` quantized release of **Void** for use with **ComfyUI-NetflixVoid**. Node implementation: https://github.com/jaskirat05/ComfyUI-NetflixVoid ## Overview This model package is intended for users running the Void workflow through the ComfyUI-NetflixVoid node implementation. It includes the quantized transformer checkpoints and is designed for local inference on supported hardware. ## Requirements - Minimum VRAM: `16 GB` ## Installation Place the model files into the corresponding ComfyUI directories shown below. ### Transformer Copy the transformer checkpoint files from the `transformer/` folder in this Hugging Face repository to: ```text models/checkpoints/ ``` Files: - `void_pass1.safetensors` - `void_pass2.safetensors` ### Text Encoder Copy the text encoder files to: ```text models/text_encoders/void/ ``` Files: - `config.json` - `model-00001-of-00002.safetensors` - `model-00002-of-00002.safetensors` - `model.safetensors.index.json` ### VAE Copy the VAE files to: ```text models/vae/ ``` File: - `diffusion_pytorch_model.safetensors` ## VLM Dependency This setup uses **Gemma 4** for VLM-based analysis. The dependency is downloaded automatically by the node implementation, so no manual installation is required for that component. ## Example Workflow Example workflows are available in the `examples` directory of the ComfyUI-NetflixVoid repository: https://github.com/jaskirat05/ComfyUI-NetflixVoid/tree/main/examples ## Related Repository Main implementation repository: https://github.com/jaskirat05/ComfyUI-NetflixVoid ## Credits PQ5 quantization credit goes to **caiovicentino1** for the related Hugging Face release: https://huggingface.co/caiovicentino1/VOID-Netflix-HLWQ-Q5 ## Expected Directory Structure After downloading and placing all required files in the correct locations, your ComfyUI directory should look similar to this: ```text ComfyUI/ ├── models/ │ ├── checkpoints/ │ │ ├── void_pass1.safetensors │ │ └── void_pass2.safetensors │ ├── text_encoders/ │ │ └── void/ │ │ ├── config.json │ │ ├── model-00001-of-00002.safetensors │ │ ├── model-00002-of-00002.safetensors │ │ └── model.safetensors.index.json │ └── vae...

Source context: 0 downloads · 0 likes · Library diffusers · Repo jaski055/ComfyUI-NetflixVoid