Instructions to use XuejiFang/LeWAM with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use XuejiFang/LeWAM with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("XuejiFang/LeWAM", 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 vision_encoder/preprocessor_config.json from XuejiFang/LeWAM: direct link, hf CLI and curl.
- Browser
- Download file 325 Bytes
-
https://huggingface.co/XuejiFang/LeWAM/resolve/main/vision_encoder/preprocessor_config.json
- Command line
-
hf download hf://XuejiFang/LeWAM/vision_encoder/preprocessor_config.json
-
curl -L -o preprocessor_config.json https://huggingface.co/XuejiFang/LeWAM/resolve/main/vision_encoder/preprocessor_config.json
325 Bytes
| { | |
| "do_normalize": true, | |
| "do_rescale": true, | |
| "do_resize": true, | |
| "image_mean": [ | |
| 0.5, | |
| 0.5, | |
| 0.5 | |
| ], | |
| "image_processor_type": "ViTImageProcessor", | |
| "image_std": [ | |
| 0.5, | |
| 0.5, | |
| 0.5 | |
| ], | |
| "resample": 2, | |
| "rescale_factor": 0.00392156862745098, | |
| "size": { | |
| "height": 224, | |
| "width": 224 | |
| } | |
| } | |