Instructions to use 43ntropy/NEvo with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use 43ntropy/NEvo with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("43ntropy/NEvo", 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
| from .asset_scorer import AssetScoreRecord, AssetScorer, score_image_asset, score_video_asset | |
| from .base import Scorer | |
| from .encoder_preprocess import EncoderPreparedInput, EncoderPreprocessSpec, prepare_image_for_encoder, prepare_video_for_encoder | |
| from .encoder_scorer import EncoderScorer | |
| from .objectives import build_objective | |
| from .robust_transform import RobustTransformScorer, RobustTransformSpec, apply_robust_transform | |
| from .targets import TargetSpec, parse_target | |
| __all__ = [ | |
| "AssetScoreRecord", | |
| "AssetScorer", | |
| "EncoderPreparedInput", | |
| "EncoderPreprocessSpec", | |
| "Scorer", | |
| "EncoderScorer", | |
| "RobustTransformScorer", | |
| "RobustTransformSpec", | |
| "TargetSpec", | |
| "apply_robust_transform", | |
| "build_objective", | |
| "parse_target", | |
| "prepare_image_for_encoder", | |
| "prepare_video_for_encoder", | |
| "score_image_asset", | |
| "score_video_asset", | |
| ] | |