# HiDream-I1

**Repository Path**: mirrors/HiDream-I1

## Basic Information

- **Project Name**: HiDream-I1
- **Description**: HiDream-I1 是开源 AI 图像生成大模型，在图像质量、语义理解、艺术表现三大维度刷新行业纪录，实现图像的多风格生成，涵盖动漫、肖像、科幻等场景
- **Primary Language**: Python
- **License**: MIT
- **Default Branch**: main
- **Homepage**: https://www.oschina.net/p/hidream-i1
- **GVP Project**: No

## Statistics

- **Stars**: 1
- **Forks**: 0
- **Created**: 2025-04-18
- **Last Updated**: 2025-11-01

## Categories & Tags

**Categories**: Uncategorized

**Tags**: None

## README

# HiDream-I1

![HiDream-I1 Demo](assets/demo.jpg)



`HiDream-I1` is a new open-source image generative foundation model with 17B parameters that achieves state-of-the-art image generation quality within seconds.

<span style="color: #FF5733; font-weight: bold">For more features and to experience the full capabilities of our product, please visit [https://vivago.ai/](https://vivago.ai/).</span>

## Project Updates
- 🌟 **July 16, 2025**: We've open-sourced the updated image editing model [**HiDream-E1-1**](https://github.com/HiDream-ai/HiDream-E1).
- 📝 **May 28, 2025**: We've released our technical report [HiDream-I1: A High-Efficient Image Generative Foundation Model with Sparse Diffusion Transformer](https://arxiv.org/abs/2505.22705).
- 🚀 **April 28, 2025**: We've open-sourced the instruction-based-image-editing model [**HiDream-E1-Full**](https://github.com/HiDream-ai/HiDream-E1). Experience at [https://huggingface.co/spaces/HiDream-ai/HiDream-E1-Full](https://huggingface.co/spaces/HiDream-ai/HiDream-E1-Full)!. 
- 🤗 **April 11, 2025**: HiDream is now officially supported in the `diffusers` library. Check out the docs [here](https://huggingface.co/docs/diffusers/main/en/api/pipelines/hidream).
- 🤗 **April 8, 2025**: We've launched a Hugging Face Space for **HiDream-I1-Dev**. Experience our model firsthand at [https://huggingface.co/spaces/HiDream-ai/HiDream-I1-Dev](https://huggingface.co/spaces/HiDream-ai/HiDream-I1-Dev)!
- 🚀 **April 7, 2025**: We've open-sourced the text-to-image model **HiDream-I1**. 


## Models

We offer both the full version and distilled models. For more information about the models, please refer to the link under Usage.

| Name            | Script                                             | Inference Steps | HuggingFace repo       |
| --------------- | -------------------------------------------------- | --------------- | ---------------------- |
| HiDream-I1-Full | [inference.py](./inference.py)                     | 50              | 🤗 [HiDream-I1-Full](https://huggingface.co/HiDream-ai/HiDream-I1-Full)  |
| HiDream-I1-Dev  | [inference.py](./inference.py)                     | 28              | 🤗 [HiDream-I1-Dev](https://huggingface.co/HiDream-ai/HiDream-I1-Dev) |
| HiDream-I1-Fast | [inference.py](./inference.py)                     | 16              | 🤗 [HiDream-I1-Fast](https://huggingface.co/HiDream-ai/HiDream-I1-Fast) |


## Quick Start
Please make sure you have installed [Flash Attention](https://github.com/Dao-AILab/flash-attention). We recommend CUDA versions 12.4 for the manual installation.

```sh
pip install -r requirements.txt
pip install -U flash-attn --no-build-isolation
```

Then you can run the inference scripts to generate images:

``` python 
# For full model inference
python ./inference.py --model_type full

# For distilled dev model inference
python ./inference.py --model_type dev

# For distilled fast model inference
python ./inference.py --model_type fast
```

> [!NOTE]
> The inference script will try to automatically download `meta-llama/Llama-3.1-8B-Instruct` model files. You need to [agree to the license of the Llama model](https://huggingface.co/meta-llama/Llama-3.1-8B-Instruct) on your HuggingFace account and login using `huggingface-cli login` in order to use the automatic downloader.

## Gradio Demo

We also provide a Gradio demo for interactive image generation. You can run the demo with:

``` python
python gradio_demo.py 
```

## Inference with Diffusers

We recommend install Diffusers from source for better compatibility.

```shell
pip install git+https://github.com/huggingface/diffusers.git
```

Then you can inference **HiDream-I1** with the following command:

```python
import torch
from transformers import PreTrainedTokenizerFast, LlamaForCausalLM
from diffusers import HiDreamImagePipeline
tokenizer_4 = PreTrainedTokenizerFast.from_pretrained("meta-llama/Meta-Llama-3.1-8B-Instruct")
text_encoder_4 = LlamaForCausalLM.from_pretrained(
    "meta-llama/Meta-Llama-3.1-8B-Instruct",
    output_hidden_states=True,
    output_attentions=True,
    torch_dtype=torch.bfloat16,
)

pipe = HiDreamImagePipeline.from_pretrained(
    "HiDream-ai/HiDream-I1-Full",  # "HiDream-ai/HiDream-I1-Dev" | "HiDream-ai/HiDream-I1-Fast"
    tokenizer_4=tokenizer_4,
    text_encoder_4=text_encoder_4,
    torch_dtype=torch.bfloat16,
)

pipe = pipe.to('cuda')

image = pipe(
    'A cat holding a sign that says "HiDream.ai".',
    height=1024,
    width=1024,
    guidance_scale=5.0,  # 0.0 for Dev&Fast
    num_inference_steps=50,  # 28 for Dev and 16 for Fast
    generator=torch.Generator("cuda").manual_seed(0),
).images[0]
image.save("output.png")
```

## Evaluation Metrics

### DPG-Bench
| Model          | Overall   | Global | Entity | Attribute | Relation | Other |
| -------------- | --------- | ------ | ------ | --------- | -------- | ----- |
| PixArt-alpha   | 71.11     | 74.97  | 79.32  | 78.60     | 82.57    | 76.96 |
| SDXL           | 74.65     | 83.27  | 82.43  | 80.91     | 86.76    | 80.41 |
| DALL-E 3       | 83.50     | 90.97  | 89.61  | 88.39     | 90.58    | 89.83 |
| Flux.1-dev     | 83.79     | 85.80  | 86.79  | 89.98     | 90.04    | 89.90 |
| SD3-Medium     | 84.08     | 87.90  | 91.01  | 88.83     | 80.70    | 88.68 |
| Janus-Pro-7B   | 84.19     | 86.90  | 88.90  | 89.40     | 89.32    | 89.48 |
| CogView4-6B    | 85.13     | 83.85  | 90.35  | 91.17     | 91.14    | 87.29 |
| **HiDream-I1** | **85.89** | 76.44  | 90.22  | 89.48     | 93.74    | 91.83 |

### GenEval

| Model          | Overall  | Single Obj. | Two Obj. | Counting | Colors | Position | Color attribution |
| -------------- | -------- | ----------- | -------- | -------- | ------ | -------- | ----------------- |
| SDXL           | 0.55     | 0.98        | 0.74     | 0.39     | 0.85   | 0.15     | 0.23              |
| PixArt-alpha   | 0.48     | 0.98        | 0.50     | 0.44     | 0.80   | 0.08     | 0.07              |
| Flux.1-dev     | 0.66     | 0.98        | 0.79     | 0.73     | 0.77   | 0.22     | 0.45              |
| DALL-E 3       | 0.67     | 0.96        | 0.87     | 0.47     | 0.83   | 0.43     | 0.45              |
| CogView4-6B    | 0.73     | 0.99        | 0.86     | 0.66     | 0.79   | 0.48     | 0.58              |
| SD3-Medium     | 0.74     | 0.99        | 0.94     | 0.72     | 0.89   | 0.33     | 0.60              |
| Janus-Pro-7B   | 0.80     | 0.99        | 0.89     | 0.59     | 0.90   | 0.79     | 0.66              |
| **HiDream-I1** | **0.83** | 1.00        | 0.98     | 0.79     | 0.91   | 0.60     | 0.72              |

### HPSv2.1 benchmark

| Model                 | Averaged  | Animation | Concept-art | Painting | Photo |
| --------------------- | --------- | --------- | ----------- | -------- | ----- |
| Stable Diffusion v2.0 | 26.38     | 27.09     | 26.02       | 25.68    | 26.73 |
| Midjourney V6         | 30.29     | 32.02     | 30.29       | 29.74    | 29.10 |
| SDXL                  | 30.64     | 32.84     | 31.36       | 30.86    | 27.48 |
| Dall-E3               | 31.44     | 32.39     | 31.09       | 31.18    | 31.09 |
| SD3                   | 31.53     | 32.60     | 31.82       | 32.06    | 29.62 |
| Midjourney V5         | 32.33     | 34.05     | 32.47       | 32.24    | 30.56 |
| CogView4-6B           | 32.31     | 33.23     | 32.60       | 32.89    | 30.52 |
| Flux.1-dev            | 32.47     | 33.87     | 32.27       | 32.62    | 31.11 |
| stable cascade        | 32.95     | 34.58     | 33.13       | 33.29    | 30.78 |
| **HiDream-I1**        | **33.82** | 35.05     | 33.74       | 33.88    | 32.61 |

## License

The code in this repository and the HiDream-I1 models are licensed under [MIT License](./LICENSE).

## Citation

```bibtex
@article{hidreami1technicalreport,
  title={HiDream-I1: A High-Efficient Image Generative Foundation Model with Sparse Diffusion Transformer},
  author={Cai, Qi and Chen, Jingwen and Chen, Yang and Li, Yehao and Long, Fuchen and Pan, Yingwei and Qiu, Zhaofan and Zhang, Yiheng and Gao, Fengbin and Xu, Peihan and others},
  journal={arXiv preprint arXiv:2505.22705},
  year={2025}
}
```