Instructions to use phi-lab-rice/GRADE with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use phi-lab-rice/GRADE with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("phi-lab-rice/GRADE", 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
Commit History
15 days ago
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Match model README to corrected GitHub review-fixes README
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Remove review status link from model card
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Remove review status document from model repository
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Record dataset README PR and remaining author actions
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Remove stale conflicting requirements from earlier release
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Link review status from model card
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Document artifact review verification and open archive items
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Fix direct no-gradient ablation entry point
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Release all GRADE models, checkpoints, and reviewed evaluation code (part 2)
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Release all GRADE models, checkpoints, and reviewed evaluation code
Verified signatureAdd all 15 model paths and 20 safetensors files; include E1/E2 reproduction code, setup instructions, fixes for reviewer findings, and checkpoint SHA-256 manifest.0e150d6 -
Release GRADE full model and checkpoints
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initial commit
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