Instructions to use tugrulv89/image21-evaluation-cache with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use tugrulv89/image21-evaluation-cache with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("tugrulv89/image21-evaluation-cache", 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 History
20 days ago
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Match research worker to Git 4ba59dcc3
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Use official CPU offload and verified pipeline signature for 48 GB evaluation
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Use pinned RunPod host cache offline and record real GPU memory
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Align documented public evaluation scope with Git worker
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Pin official Image 2.1 evaluation weights and matching research worker
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initial commit
Verified signature7c82db6