Instructions to use hugaagg/IR_expeiment with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use hugaagg/IR_expeiment with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("hugaagg/IR_expeiment", 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 PART1/CodeFormer/facelib/utils/__init__.py from hugaagg/IR_expeiment: direct link, hf CLI and curl.
- Browser
- Download file 396 Bytes
-
https://huggingface.co/hugaagg/IR_expeiment/resolve/main/PART1/CodeFormer/facelib/utils/__init__.py
- Command line
-
hf download hf://hugaagg/IR_expeiment/PART1/CodeFormer/facelib/utils/__init__.py
-
curl -L -o __init__.py https://huggingface.co/hugaagg/IR_expeiment/resolve/main/PART1/CodeFormer/facelib/utils/__init__.py
396 Bytes
| from .face_utils import align_crop_face_landmarks, compute_increased_bbox, get_valid_bboxes, paste_face_back | |
| from .misc import img2tensor, load_file_from_url, download_pretrained_models, scandir | |
| __all__ = [ | |
| 'align_crop_face_landmarks', 'compute_increased_bbox', 'get_valid_bboxes', 'load_file_from_url', | |
| 'download_pretrained_models', 'paste_face_back', 'img2tensor', 'scandir' | |
| ] | |