Instructions to use ixim/ERNIE-Image-INT8 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use ixim/ERNIE-Image-INT8 with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("ixim/ERNIE-Image-INT8", dtype=torch.bfloat16, device_map="cuda") prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
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{
"name": "poster_text",
"prompt": "A premium technology conference poster with both Chinese and English headline text, sharp typography, asymmetric geometric grid, amber accent lighting, and a clean editorial finish.",
"recommended_size": "848x1264"
},
{
"name": "urban_photo",
"prompt": "A cinematic urban street photograph at dusk with long shadows, volumetric light beams, tiled pavement, a cyclist moving away from camera, and warm backlighting.",
"recommended_size": "848x1264"
},
{
"name": "comic_storyboard",
"prompt": "A four-panel storyboard comic with consistent characters, readable caption areas, dramatic color scripting, and clear panel separation.",
"recommended_size": "1200x896"
},
{
"name": "product_layout",
"prompt": "A product launch hero image featuring a sleek wearable device, editorial layout composition, bold sans-serif headline area, and restrained industrial materials.",
"recommended_size": "1264x848"
},
{
"name": "infographic_scene",
"prompt": "An infographic-style scene with chart cards, iconography, readable labels, and precise layout alignment suitable for presentation slides.",
"recommended_size": "1024x1024"
}
]
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