Instructions to use jaski055/ComfyUI-NetflixVoid with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use jaski055/ComfyUI-NetflixVoid with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("jaski055/ComfyUI-NetflixVoid", dtype=torch.bfloat16, device_map="cuda") prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
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Verified signature# ComfyUI-NetflixVoid Custom ComfyUI nodes for the VOID workflow: 1. Stage 1: black mask 2. Stage 2: VLM prep + parse 3. Stage 3: grey mask 4. Stage 4: quadmask 5. Stage 5: modular PQ5 inference ## Included nodes - `VOID Load SAM3 Model` - `VOID Export Black Mask` - `VOID Prepare VLM Analysis` - `VOID Parse VLM Analysis` - `VOID Build Grey Mask` - `VOID Combine Quadmask` - `VOID Gemma 4 E2B Video Prompt` - `VOID PQ5 Load Model` - `VOID PQ5 Settings` - `VOID PQ5 Encode Prompt` - `VOID PQ5 Encode Video` - `VOID PQ5 Encode Quadmask` - `VOID PQ5 Sampler` - `VOID PQ5 Decode Video` - `VOID PQ5 Unload Cache` ## PQ5 assets and models This repo now uses a modular PQ5 layout. Required locations: - Transformer checkpoint: `ComfyUI/models/checkpoints` (select in `VOID PQ5 Load Model`) - VAE checkpoint: `ComfyUI/models/vae` (select in `VOID PQ5 Load Model`) - Text encoder folder: `ComfyUI/models/text_encoders/void` - Repo-local PQ5 configs/tokenizer/scheduler: `ComfyUI-NetflixVoid/pq5_asset…60cfc5c -
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