File size: 3,064 Bytes
5545c60 1c42815 a12650f 5545c60 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 |
---
license: apache-2.0
language:
- en
base_model:
- OpenIXCLab/SeC-4B
pipeline_tag: image-segmentation
library_name: transformers
---
# SeC-4B Model Files - Multiple Precision Formats
Single-file model formats for the **SeC (Segment Concept)** video object segmentation model, optimized for use with [ComfyUI SeC Nodes](https://github.com/9nate-drake/Comfyui-SecNodes).
## Model Formats
| Format | Size | Description | GPU Requirements |
|--------|------|-------------|------------------|
| **SeC-4B-fp16.safetensors** | 7.35 GB | Recommended - Best balance of quality and size | All CUDA GPUs |
| **SeC-4B-fp8.safetensors** | 3.97 GB | VRAM-constrained systems (saves 1.5-2GB VRAM) | RTX 30 series or newer |
| **SeC-4B-bf16.safetensors** | 7.35 GB | Alternative to FP16 | All CUDA GPUs |
| **SeC-4B-fp32.safetensors** | 14.14 GB | Full precision | All CUDA GPUs |
## What is SeC?
**SeC (Segment Concept)** uses Large Vision-Language Models for video object segmentation, achieving **+11.8 points** improvement over SAM 2.1 on complex semantic scenarios (SeCVOS benchmark).
Key features:
- Concept-driven tracking with semantic understanding
- Handles occlusions and appearance changes
- Bidirectional tracking support
- State-of-the-art performance on multiple benchmarks
## Usage
These models are designed for use with the [ComfyUI SeC Nodes](https://github.com/9nate-drake/Comfyui-SecNodes) custom nodes.
**Installation:**
1. Download your preferred model format
2. Place in `ComfyUI/models/sams/`
3. Install [ComfyUI SeC Nodes](https://github.com/9nate-drake/Comfyui-SecNodes)
4. The model will be automatically detected and available in the SeC Model Loader
## Original Model
These are converted single-file versions of the original model:
- **Original Repository**: [OpenIXCLab/SeC-4B](https://huggingface.co/OpenIXCLab/SeC-4B)
- **Paper**: [arXiv:2507.15852](https://arxiv.org/abs/2507.15852)
- **Official Implementation**: [github.com/OpenIXCLab/SeC](https://github.com/OpenIXCLab/SeC)
## Credits
**Original Model**: Developed by OpenIXCLab
- Model architecture and weights: Apache 2.0 License
- Paper: Zhang et al. "SeC: Advancing Complex Video Object Segmentation via Progressive Concept Construction"
**Single-File Conversions**: Created for [ComfyUI SeC Nodes](https://github.com/9nate-drake/Comfyui-SecNodes)
- Conversion script and ComfyUI integration: [9nate-drake](https://github.com/9nate-drake)
- FP8 quantization support via [torchao](https://github.com/pytorch/ao)
## License
Apache 2.0 (same as original SeC-4B model)
## Citation
If you use this model in your research, please cite the original SeC paper:
```bibtex
@article{zhang2025sec,
title = {SeC: Advancing Complex Video Object Segmentation via Progressive Concept Construction},
author = {Zhixiong Zhang and Shuangrui Ding and Xiaoyi Dong and Songxin He and
Jianfan Lin and Junsong Tang and Yuhang Zang and Yuhang Cao and
Dahua Lin and Jiaqi Wang},
journal = {arXiv preprint arXiv:2507.15852},
year = {2025}
}
``` |