Instructions to use Efficient-Large-Model/SANA-WM_bidirectional-diffusers with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Efficient-Large-Model/SANA-WM_bidirectional-diffusers with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("Efficient-Large-Model/SANA-WM_bidirectional-diffusers", 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 text_encoder/generation_config.json from Efficient-Large-Model/SANA-WM_bidirectional-diffusers: direct link, hf CLI and curl.
- Browser
- Download file 187 Bytes
-
https://huggingface.co/Efficient-Large-Model/SANA-WM_bidirectional-diffusers/resolve/main/text_encoder/generation_config.json
- Command line
-
hf download hf://Efficient-Large-Model/SANA-WM_bidirectional-diffusers/text_encoder/generation_config.json
-
curl -L -o generation_config.json https://huggingface.co/Efficient-Large-Model/SANA-WM_bidirectional-diffusers/resolve/main/text_encoder/generation_config.json
187 Bytes
| { | |
| "_from_model_config": true, | |
| "bos_token_id": 2, | |
| "cache_implementation": "hybrid", | |
| "eos_token_id": [ | |
| 1, | |
| 107 | |
| ], | |
| "pad_token_id": 0, | |
| "transformers_version": "4.57.3" | |
| } | |