Instructions to use baidu/ERNIE-Image with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use baidu/ERNIE-Image with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("baidu/ERNIE-Image", dtype=torch.bfloat16, device_map="cuda") prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k" image = pipe(prompt).images[0] - Inference
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
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<a href="https://huggingface.co/Baidu/ERNIE-Image">🤗 ERNIE-Image</a> |
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<a href="https://huggingface.co/Baidu/ERNIE-Image-Turbo">🤗 ERNIE-Image-Turbo</a> |
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ERNIE-Image is an open text-to-image generation model developed by the ERNIE-Image team at Baidu. It is built on a single-stream Diffusion Transformer (DiT) and paired with a lightweight Prompt Enhancer that expands brief user inputs into richer structured descriptions. With only 8B DiT parameters, it reaches state-of-the-art performance among open-weight text-to-image models. The model is designed not only for strong visual quality, but also for controllability in practical generation scenarios where accurate content realization matters as much as aesthetics. In particular, ERNIE-Image performs strongly on complex instruction following, text rendering, and structured image generation, making it well suited for commercial posters, comics, multi-panel layouts, and other content creation tasks that require both visual quality and precise control. It also supports a broad range of visual styles, including realistic photography, design-oriented imagery, and more stylized aesthetic outputs.
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<a href="https://huggingface.co/Baidu/ERNIE-Image">🤗 ERNIE-Image</a> |
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<a href="https://huggingface.co/Baidu/ERNIE-Image-Turbo">🤗 ERNIE-Image-Turbo</a> |
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<a href="https://huggingface.co/spaces/baidu/ERNIE-Image">🖥️ Huggingface Demo</a> |
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<a href="https://aistudio.baidu.com/application/detail/179775">🖥️ AI Studio Demo</a> |
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<a href="https://yiyan.baidu.com/blog/posts/ernie-image">📖 Blog</a> |
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<a href="https://ernieimageprompt.com/">🖼️ Art Gallery</a>
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<a href="https://github.com/baidu/ERNIE-Image/blob/main/assets/contacts/WeChat.jpg">💬 WeChat(微信)</a> |
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<a href="https://discord.gg/ByUTbjfG5k">🫨 Discord</a> |
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<a href="https://x.com/ErnieforDevs">🏷️ X</a>
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ERNIE-Image is an open text-to-image generation model developed by the ERNIE-Image team at Baidu. It is built on a single-stream Diffusion Transformer (DiT) and paired with a lightweight Prompt Enhancer that expands brief user inputs into richer structured descriptions. With only 8B DiT parameters, it reaches state-of-the-art performance among open-weight text-to-image models. The model is designed not only for strong visual quality, but also for controllability in practical generation scenarios where accurate content realization matters as much as aesthetics. In particular, ERNIE-Image performs strongly on complex instruction following, text rendering, and structured image generation, making it well suited for commercial posters, comics, multi-panel layouts, and other content creation tasks that require both visual quality and precise control. It also supports a broad range of visual styles, including realistic photography, design-oriented imagery, and more stylized aesthetic outputs.
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