Instructions to use inclusionAI/Ming-Lite-Uni with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use inclusionAI/Ming-Lite-Uni with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("inclusionAI/Ming-Lite-Uni", dtype=torch.bfloat16, device_map="cuda") prompt = "Hi, what can you help me with?" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
Download vae/config.json from inclusionAI/Ming-Lite-Uni: direct link, hf CLI and curl.
- Browser
- Download file 1.28 kB
-
https://huggingface.co/inclusionAI/Ming-Lite-Uni/resolve/main/vae/config.json
- Command line
-
hf download hf://inclusionAI/Ming-Lite-Uni/vae/config.json
-
curl -L -o config.json https://huggingface.co/inclusionAI/Ming-Lite-Uni/resolve/main/vae/config.json
1.28 kB
| { | |
| "_class_name": "AutoencoderDC", | |
| "_diffusers_version": "0.33.0.dev0", | |
| "_name_or_path": "mit-han-lab/dc-ae-f32c32-sana-1.1-diffusers", | |
| "attention_head_dim": 32, | |
| "decoder_act_fns": "silu", | |
| "decoder_block_out_channels": [ | |
| 128, | |
| 256, | |
| 512, | |
| 512, | |
| 1024, | |
| 1024 | |
| ], | |
| "decoder_block_types": [ | |
| "ResBlock", | |
| "ResBlock", | |
| "ResBlock", | |
| "EfficientViTBlock", | |
| "EfficientViTBlock", | |
| "EfficientViTBlock" | |
| ], | |
| "decoder_layers_per_block": [ | |
| 3, | |
| 3, | |
| 3, | |
| 3, | |
| 3, | |
| 3 | |
| ], | |
| "decoder_norm_types": "rms_norm", | |
| "decoder_qkv_multiscales": [ | |
| [], | |
| [], | |
| [], | |
| [ | |
| 5 | |
| ], | |
| [ | |
| 5 | |
| ], | |
| [ | |
| 5 | |
| ] | |
| ], | |
| "downsample_block_type": "Conv", | |
| "encoder_block_out_channels": [ | |
| 128, | |
| 256, | |
| 512, | |
| 512, | |
| 1024, | |
| 1024 | |
| ], | |
| "encoder_block_types": [ | |
| "ResBlock", | |
| "ResBlock", | |
| "ResBlock", | |
| "EfficientViTBlock", | |
| "EfficientViTBlock", | |
| "EfficientViTBlock" | |
| ], | |
| "encoder_layers_per_block": [ | |
| 2, | |
| 2, | |
| 2, | |
| 3, | |
| 3, | |
| 3 | |
| ], | |
| "encoder_qkv_multiscales": [ | |
| [], | |
| [], | |
| [], | |
| [ | |
| 5 | |
| ], | |
| [ | |
| 5 | |
| ], | |
| [ | |
| 5 | |
| ] | |
| ], | |
| "in_channels": 3, | |
| "latent_channels": 32, | |
| "scaling_factor": 0.41407, | |
| "upsample_block_type": "interpolate" | |
| } | |