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
- Draw Things
- DiffusionBee
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### Model Description
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1. Overview
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**ERNIE-Image** is a text-to-image generation model developed by the ERNIE team at Baidu.
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In terms of image quality, ERNIE-Image is on par with current state-of-the-art models. It demonstrates significant advantages in handling complex instructions, particularly in tasks that require **accurate text rendering** and **knowledge-intensive generation**.
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### Model Description
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**ERNIE-Image** is a text-to-image generation model developed by the ERNIE team at Baidu.
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In terms of image quality, ERNIE-Image is on par with current state-of-the-art models. It demonstrates significant advantages in handling complex instructions, particularly in tasks that require **accurate text rendering** and **knowledge-intensive generation**.
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