Text-to-Image
Diffusers
ONNX
English
StableDiffusionPipeline
stable-diffusion
stable-diffusion-diffusers
Instructions to use TheyCallMeHex/Mo-Di-Diffusion-ONNX with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use TheyCallMeHex/Mo-Di-Diffusion-ONNX with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("TheyCallMeHex/Mo-Di-Diffusion-ONNX", 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
Commit ·
7ce4b6b
1
Parent(s): 660ccfe
Added cliptokenizer file
Browse files- tokenizer/model.onnx +3 -0
tokenizer/model.onnx
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version https://git-lfs.github.com/spec/v1
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oid sha256:52af50d264d702c351484aabf62c64abe61f59d6a6d2c508a3e797e23dc1e008
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size 1683168
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