initial model card

README.md

@@ -1,3 +1,124 @@
----
-license: apache-2.0
----
+---
+license: other
+license_name: tencent-hunyuan-community
+license_link: https://huggingface.co/tencent/HunyuanImage-3.0/blob/main/LICENSE.txt
+tags:
+  - text-to-image
+  - hunyuan
+  - quantization
+  - int8
+  - comfyui
+pipeline_tag: text-to-image
+---
+
+# Hunyuan Image 3.0 - INT8 Quantized
+
+This is an **INT8 quantized version** of Tencent's [HunyuanImage-3.0](https://huggingface.co/tencent/HunyuanImage-3.0) model, optimized for high-end GPU workflows without CPU offloading.
+
+## Model Description
+
+INT8 quantization of the Hunyuan Image 3.0 text-to-image diffusion transformer, providing a balance between the full BF16 precision and more aggressive NF4 quantization. This version maintains excellent image quality while reducing memory requirements.
+
+**Key Features:**
+- 🎯 High quality output comparable to BF16
+- 💾 ~80GB VRAM required (fits RTX 6000 Ada/Blackwell)
+- ⚡ ~3.5 minutes generation time at base resolution
+- 🔧 Designed for ComfyUI workflows
+
+## VRAM Requirements
+
+| Phase | VRAM Usage |
+|-------|------------|
+| Weight Loading | ~80 GB |
+| Inference (additional) | ~12-20 GB |
+| **Total** | **~92-100 GB** |
+
+**Recommended Hardware:**
+- NVIDIA RTX 6000 Ada (48GB) - requires model split/offload
+- NVIDIA RTX 6000 Blackwell (96GB) - fits entirely in VRAM ✅
+- Multi-GPU setups with 80GB+ combined VRAM
+
+## Usage
+
+### ComfyUI (Recommended)
+
+This model is designed to work with the [Comfy_HunyuanImage3](https://github.com/EricRollei/Comfy_HunyuanImage3) custom nodes:
+```bash
+cd ComfyUI/custom_nodes
+git clone https://github.com/EricRollei/Comfy_HunyuanImage3
+```
+
+Install the nodes and download this model to your ComfyUI models directory. The nodes handle INT8 loading automatically.
+
+### Direct Usage
+```python
+# INT8 weights can be loaded with standard torch quantization
+# See the ComfyUI nodes for reference implementation
+```
+
+## Performance
+
+- **Generation Time**: ~3.5 minutes for base resolution (1024x1024)
+- **Weight Loading**: ~60 seconds (one-time per session)
+- **Quality**: Excellent - minimal degradation from BF16
+- **Speed**: Faster inference than BF16 due to reduced memory bandwidth
+
+## Quantization Details
+
+- **Method**: INT8 per-channel quantization
+- **Target**: Hunyuan Image 3.0 transformer backbone
+- **Precision Loss**: Minimal - image quality remains high
+- **Trade-off**: Middle ground between NF4 (lower quality) and BF16 (highest VRAM)
+
+## Original Model
+
+This is a quantized derivative of [Tencent's HunyuanImage-3.0](https://huggingface.co/tencent/HunyuanImage-3.0).
+
+**Original Model Details:**
+- Architecture: Diffusion Transformer
+- Resolution: Up to 2048x2048
+- Language Support: English and Chinese prompts
+- License: [Tencent Hunyuan Community License](https://huggingface.co/tencent/HunyuanImage-3.0/blob/main/LICENSE.txt)
+
+Please review the original model card and license for full details on capabilities and restrictions.
+
+## Limitations
+
+- Requires high-end professional GPU (80GB+ VRAM)
+- Not suitable for consumer GPUs (4090, 5090) without further optimization
+- INT8 quantization may introduce minor quality differences in edge cases
+- Loading time adds ~1 minute overhead to first generation
+
+## Credits
+
+**Original Model**: [Tencent Hunyuan Team](https://huggingface.co/tencent)
+**Quantization**: Eric Rollei
+**ComfyUI Integration**: [Comfy_HunyuanImage3](https://github.com/EricRollei/Comfy_HunyuanImage3)
+
+## License
+
+This model inherits the license from the original Hunyuan Image 3.0 model:
+- **License**: [Tencent Hunyuan Community License](https://huggingface.co/tencent/HunyuanImage-3.0/blob/main/LICENSE.txt)
+- Please review the original license for commercial use restrictions and requirements
+
+## Citation
+```bibtex
+@misc{hunyuan-image-3-int8,
+  author = {Rollei, Eric},
+  title = {Hunyuan Image 3.0 INT8 Quantized},
+  year = {2024},
+  publisher = {Hugging Face},
+  howpublished = {\url{https://huggingface.co/[YOUR_USERNAME]/[MODEL_NAME]}}
+}
+```
+
+Original model citation:
+```bibtex
+@misc{tencent2024hunyuan,
+  title={Hunyuan Image 3.0},
+  author={Tencent Hunyuan Team},
+  year={2024},
+  publisher={Hugging Face},
+  howpublished={\url{https://huggingface.co/tencent/HunyuanImage-3.0}}
+}
+```