Joy Caption Two - PixelaiLabs Edition

By PixelailabsView on GitHub →

A fully automated ComfyUI custom node that uses Joy Caption Alpha Two to generate high-quality image captions. Perfect for: LoRA/model training dataset preparation, Image tagging and organization, NSFW content captioning, Batch processing large image collections

How much VRAM does Joy Caption Two - PixelaiLabs Edition require?

Direct Answer: The ComfyUI node Joy Caption Two - PixelaiLabs Edition requires a minimum base VRAM of 128MB and is optimized for GPUs with at least 4GB of VRAM. Low VRAM mode is fully supported for resource-constrained setups.

High (2-4GB)
Base VRAM:
128MB (0.1GB)
Recommended GPU:
4GB+ VRAM
Low VRAM Mode:
✓ Supported
Estimation Confidence:
MEDIUM

Interactive VRAM Compatibility Estimator

Estimated Total VRAM: 3.00 GBTarget: 8 GB
✅ Comfortable Fit

Your GPU has plenty of headroom. You can run this node safely with your active configurations!

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What Python packages are required for Joy Caption Two - PixelaiLabs Edition?

Direct Answer: Running Joy Caption Two - PixelaiLabs Edition requires installing the following Python package dependencies: accelerate>=0.25.0, bitsandbytes>=0.43.0, hf_xet>=0.3.0, huggingface_hub>=0.20.0, numpy>=1.24.0, pillow>=10.0.0, protobuf>=3.20.0, sentencepiece>=0.1.99, torch>=2.0.0, transformers>=4.44.0. This node specifically requires PyTorch version 2.0.0 or newer.

requirements.txt
accelerate>=0.25.0
bitsandbytes>=0.43.0
hf_xet>=0.3.0
huggingface_hub>=0.20.0
numpy>=1.24.0
pillow>=10.0.0
protobuf>=3.20.0
sentencepiece>=0.1.99
torch>=2.0.0
transformers>=4.44.0

Interactive Setup & Dependency Resolver

Operating System:
Environment Type:
Run this terminal command in your ComfyUI root folder:
# Loading command...

Special Environment Requirements:

Requires PyTorch version 2.0.0+.

To update PyTorch for your selected setup, run:
# Loading PyTorch command...

Frequently Asked Questions

How much VRAM does Joy Caption Two - PixelaiLabs Edition require?

Joy Caption Two - PixelaiLabs Edition requires a minimum of 128MB (0.1GB) of VRAM for base operation. For optimal performance, a GPU with at least 4GB of VRAM is recommended. This node supports low VRAM mode for resource-constrained setups.

Can I run Joy Caption Two - PixelaiLabs Edition on an RTX 3060, RTX 4070, or RTX 4090?

✅ RTX 3060 (12GB): Yes, fully compatible with 10.7GB headroom. ✅ RTX 4070 (12GB): Yes, fully compatible with 10.7GB headroom. ✅ RTX 4070 Ti (16GB): Yes, fully compatible with 14.3GB headroom. ✅ RTX 4090 (24GB): Yes, fully compatible with 21.5GB headroom

What PyTorch version does Joy Caption Two - PixelaiLabs Edition need?

Joy Caption Two - PixelaiLabs Edition requires the following PyTorch-related packages: torch>=2.0.0. Ensure your ComfyUI environment has these installed. Ensure your PyTorch installation matches your CUDA version (use torch.version.cuda to check).

What Python packages are required for Joy Caption Two - PixelaiLabs Edition?

To run Joy Caption Two - PixelaiLabs Edition, you need to install: accelerate>=0.25.0, bitsandbytes>=0.43.0, hf_xet>=0.3.0, huggingface_hub>=0.20.0, numpy>=1.24.0, pillow>=10.0.0, protobuf>=3.20.0, sentencepiece>=0.1.99, torch>=2.0.0, transformers>=4.44.0. You can install these using pip or add them to your requirements.txt file.

How can I reduce VRAM usage when running Joy Caption Two - PixelaiLabs Edition?

Joy Caption Two - PixelaiLabs Edition supports low VRAM mode. To reduce memory usage: (1) Enable --lowvram or --medvram flags in ComfyUI, (2) Reduce batch size to 1, (3) Use fp16 or fp8 precision if supported, (4) Close other GPU applications.

How do I install Joy Caption Two - PixelaiLabs Edition in ComfyUI?

To install Joy Caption Two - PixelaiLabs Edition: (1) Navigate to your ComfyUI/custom_nodes directory, (2) Clone the repository: git clone https://github.com/Pixelailabs/Joy_Caption_Two_PixelaiLabs, (3) Install dependencies: pip install -r requirements.txt (if present), (4) Restart ComfyUI. Alternatively, use ComfyUI Manager for one-click installation.