Instructions to use Cccccz/HY with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Cccccz/HY with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("Cccccz/HY", 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
Download confidence_validation/summary.json from Cccccz/HY: direct link, hf CLI and curl.
- Browser
- Download file 1.8 kB
-
https://huggingface.co/Cccccz/HY/resolve/main/confidence_validation/summary.json
- Command line
-
hf download hf://Cccccz/HY/confidence_validation/summary.json
-
curl -L -o summary.json https://huggingface.co/Cccccz/HY/resolve/main/confidence_validation/summary.json
1.8 kB
| { | |
| "c1_validation_metrics": { | |
| "P1": { | |
| "log_mae": 0.17691564559936523, | |
| "model": "Confidence C1", | |
| "pearson": 0.8829622268676758, | |
| "spearman": 0.8590718873187204, | |
| "split": "validation", | |
| "step": "P1" | |
| }, | |
| "P2": { | |
| "log_mae": 0.14503394067287445, | |
| "model": "Confidence C1", | |
| "pearson": 0.9074602127075195, | |
| "spearman": 0.8631690385373965, | |
| "split": "validation", | |
| "step": "P2" | |
| }, | |
| "P3": { | |
| "log_mae": 0.15804709494113922, | |
| "model": "Confidence C1", | |
| "pearson": 0.8872363567352295, | |
| "spearman": 0.8700319930976419, | |
| "split": "validation", | |
| "step": "P3" | |
| }, | |
| "overall": { | |
| "log_mae": 0.15999889373779297, | |
| "model": "Confidence C1", | |
| "pearson": 0.96539306640625, | |
| "spearman": 0.9529179491248462, | |
| "split": "validation", | |
| "step": "overall" | |
| } | |
| }, | |
| "gain_vs_random": 0.48957529207015615, | |
| "oracle_gap": 0.007935705508866102, | |
| "protocol": "WorldPlay fulltrain100 (8400 transitions); independent validation25 (2100 transitions); no validation tuning", | |
| "remaining_risk_at_33pct": { | |
| "Confidence C0": 0.008430036716163158, | |
| "Confidence C1": 0.004878982435911894, | |
| "Confidence C2": 0.004925357177853584, | |
| "Oracle": 0.004840569104999304, | |
| "Random": 0.009558672141283751, | |
| "Timestep-only": 0.005005753133445978 | |
| }, | |
| "routing_at_33pct": { | |
| "P1": { | |
| "selection_fraction": 0.012857142857142857, | |
| "within_step_fallback_rate": 0.012857142857142857 | |
| }, | |
| "P2": { | |
| "selection_fraction": 0.05714285714285714, | |
| "within_step_fallback_rate": 0.05714285714285714 | |
| }, | |
| "P3": { | |
| "selection_fraction": 0.93, | |
| "within_step_fallback_rate": 0.93 | |
| } | |
| }, | |
| "train_samples": 8400, | |
| "validation_samples": 2100 | |
| } | |