ComfyUI-Youtu-VL

ComfyUI-Youtu-VL
★ 13

视觉语言图像描述自动打标签低显存推理
为 ComfyUI 提供腾讯 Youtu-VL 接入，双引擎支持 transformers 与 llama.cpp，高精度或低显存推理，支持图注、自动打标签、OCR 与视觉问答。
💡 在 ComfyUI 中用 Youtu-VL 自动生成图像描述、标签或进行视觉问答。
🍴 2 Forks💻 Python🔄 2026-02-03
📦
网盘下载
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https://pan.quark.cn/s/8f9eee5e2cdb
📦 requirements.txt
transformers>=4.56.0
accelerate
pillow
torchvision
opencv-python-headless
huggingface_hub
psutil
#
GGUF
Node
Requirements
(optional)
#
pip
install
llama-cpp-python
--extra-index-url
https://abetlen.github.io/llama-cpp-python/whl/cu121
ComfyUI-Youtu-VL
📄 README

ComfyUI-Youtu-VL

ComfyUI custom nodes for Tencent Youtu-VL vision-language model.

Youtu-VL is a lightweight yet powerful 4B parameter VLM with comprehensive vision-centric capabilities including visual grounding, segmentation, depth estimation, and pose estimation.

Workflow

[](https://github.com/1038lab/ComfyUI-Youtu-VL/blob/main/LICENSE)

[](https://www.python.org/)

[](https://github.com/comfyanonymous/ComfyUI)

✨ Key Features

  • 🔥 Dual Engines: Run with standard transformers (high precision) or llama.cpp (high speed/low VRAM).
  • 🚀 Efficient & Lightweight:
  • Run FP16/BF16 reference implementation.
  • Or use 4-bit/8-bit GGUF to run on consumer GPUs (6GB+ VRAM).
  • 🧠 Smart Vision Tasks:
  • Detailed Captioning: Generate rich, descriptive prompts for Stable Diffusion.
  • Tag Generation: Auto-tag images for LoRA training.
  • OCR: Extract text from images.
  • Visual QA: Chat with your images.
  • ⚡ Zero-Config: Models auto-download on first use.

    • 📦 Installation

    Method 1: ComfyUI Manager (Recommended)

    Search for ComfyUI Youtu-VL in the Manager (Publisher: 1038lab) and click Install.

    Method 2: Manual Install

    Clone this repo into your custom_nodes folder:

    cd ComfyUI/custom_nodes/
git clone https://github.com/1038lab/ComfyUI-Youtu-VL.git
cd ComfyUI-Youtu-VL
pip install -r requirements.txt

    💡 Enable GGUF Support (Optional)

    To use the GGUF nodes for faster inference:

    pip install llama-cpp-python --extra-index-url https://abetlen.github.io/llama-cpp-python/whl/cu121

    *(Replace cu121 with your CUDA version, e.g., cu118 or metal for macOS)*

    🧩 Node Options

    1️⃣ Youtu-VL (Standard)

    *Best for precision and research.*

  • Model: Automatic download from HuggingFace (models/LLM/Youtu-VL).
  • Quantization: Built-in 8-bit/4-bit loading (via BitsAndBytes).
  • Attention: Supports Flash Attention 2 for speed.

    • 2️⃣ Youtu-VL (GGUF)

    *Best for speed and daily usage.*

  • Model: Loads .gguf files (Q4_K_M, Q8_0, F16).
  • Speed: Extremely fast CPU/GPU hybrid inference.
  • VRAM: Adjustable GPU offload layers.

    • 🎮 Capabilities & Presets

    The nodes include smart presets (in config.json) to automate common tasks:

    | Preset Mode | Description |

    | :— | :— |

    | 📝 Detailed Description | Writes a full paragraph describing lighting, composition, and subjects. |

    | 🔍 Analyze Elements | Lists key objects and layout details. |

    | 🏷️ Generate Tags | Creates comma-separated tags (Danbooru style). |

    | 📄 OCR Text | Reads and outputs visible text. |

    | 🎨 Art Style | Identifies medium, artist style, and technique. |

    | ❓ Visual QA | Ask custom questions like “What color is the…” |

    🛠 Troubleshooting

  • GGUF Node missing? -> Make sure llama-cpp-python is installed successfully.
  • Out of Memory? -> Switch to the GGUF node and select a Q4 or Q5 model.
  • Experimental Nodes: Segmentation, Depth, and Pose nodes are currently in the Beta/ folder.

    • 📄 License

  • Extension Code: Licensed under the GPL-3.0 License. Copyright © 2024 1038lab.
  • Youtu-VL Model: Licensed under the License Term of Youtu-VL by Tencent.
  • *Important: The model is NOT intended for use within the European Union and is subject to specific usage terms.*