Instructions to use duja1/ismo with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use duja1/ismo with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("duja1/ismo", dtype=torch.bfloat16, device_map="cuda") prompt = "i123smo" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
Commit History
-
Fix deprecation warning by changing `CLIPFeatureExtractor` to `CLIPImageProcessor`. (#2)
- Fix deprecation warning by changing `CLIPFeatureExtractor` to `CLIPImageProcessor`. (7c3c510e671c3fa9195890f7d3ff4df9dd593e6c)b48c539
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Upload concept_images with huggingface_hub
7ec9ac1 -
Upload with huggingface_hub
5179fc2 -
Upload the model Ismo
29f329c -
initial commit
345e939