comfyui-t5gemma-tts
ComfyUI custom nodes for T5Gemma-TTS, a multilingual text-to-speech model with voice cloning and duration control, based on the T5Gemma encoder-decoder LLM architecture.
How much VRAM does comfyui-t5gemma-tts require?
Direct Answer: The ComfyUI node comfyui-t5gemma-tts requires a minimum base VRAM of 256MB and is optimized for GPUs with at least 4GB of VRAM. Low VRAM mode is fully supported for resource-constrained setups.
- Base VRAM:
- 256MB (0.3GB)
- Recommended GPU:
- 4GB+ VRAM
- Low VRAM Mode:
- ✓ Supported
- Estimation Confidence:
- HIGH
Interactive VRAM Compatibility Estimator
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 comfyui-t5gemma-tts?
Direct Answer: Running comfyui-t5gemma-tts requires installing the following Python package dependencies: g2p_en, huggingface_hub, langdetect, pypinyin, safetensors, sentencepiece, soundfile, transformers>=4.40.0. Ensure your ComfyUI environment has these packages active before launching.
g2p_en
huggingface_hub
langdetect
pypinyin
safetensors
sentencepiece
soundfile
transformers>=4.40.0Interactive Setup & Dependency Resolver
# Loading command...Frequently Asked Questions
How much VRAM does comfyui-t5gemma-tts require?
comfyui-t5gemma-tts requires a minimum of 256MB (0.3GB) 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 comfyui-t5gemma-tts on an RTX 3060, RTX 4070, or RTX 4090?
✅ RTX 3060 (12GB): Yes, fully compatible with 10.6GB headroom. ✅ RTX 4070 (12GB): Yes, fully compatible with 10.6GB headroom. ✅ RTX 4070 Ti (16GB): Yes, fully compatible with 14.2GB headroom. ✅ RTX 4090 (24GB): Yes, fully compatible with 21.4GB headroom
What Python packages are required for comfyui-t5gemma-tts?
To run comfyui-t5gemma-tts, you need to install: g2p_en, huggingface_hub, langdetect, pypinyin, safetensors, sentencepiece, soundfile, transformers>=4.40.0. You can install these using pip or add them to your requirements.txt file.
How can I reduce VRAM usage when running comfyui-t5gemma-tts?
comfyui-t5gemma-tts 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 comfyui-t5gemma-tts in ComfyUI?
To install comfyui-t5gemma-tts: (1) Navigate to your ComfyUI/custom_nodes directory, (2) Clone the repository: git clone https://github.com/negaga53/comfyui-t5gemma-tts, (3) Install dependencies: pip install -r requirements.txt (if present), (4) Restart ComfyUI. Alternatively, use ComfyUI Manager for one-click installation.