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
Download examples/turbo_reference/zh_poster_dense_text.png from ixim/ERNIE-Image-INT8: direct link, hf CLI and curl.
- Browser
- Download file 720 kB
-
https://huggingface.co/ixim/ERNIE-Image-INT8/resolve/main/examples/turbo_reference/zh_poster_dense_text.png
- Command line
-
hf download hf://ixim/ERNIE-Image-INT8/examples/turbo_reference/zh_poster_dense_text.png
-
curl -L -o zh_poster_dense_text.png https://huggingface.co/ixim/ERNIE-Image-INT8/resolve/main/examples/turbo_reference/zh_poster_dense_text.png
720 kB

- Xet hash:
- 7881e5b916f42c402d29f508cd490033c197222b741de4ada2db30ae74847d41
- Size of remote file:
- 720 kB
- SHA256:
- 6f59f3e1083b7cea6611c89893dff648edd4ded087f4337d70217cec232ffcfb
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