Instructions to use hf-internal-testing/tiny-sana-pipe with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use hf-internal-testing/tiny-sana-pipe with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("hf-internal-testing/tiny-sana-pipe", 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
- Local Apps
- Draw Things
- DiffusionBee
| { | |
| "_class_name": "AutoencoderDC", | |
| "_diffusers_version": "0.32.0.dev0", | |
| "attention_head_dim": 2, | |
| "decoder_act_fns": "silu", | |
| "decoder_block_out_channels": [ | |
| 8, | |
| 8 | |
| ], | |
| "decoder_block_types": [ | |
| "ResBlock", | |
| "EfficientViTBlock" | |
| ], | |
| "decoder_layers_per_block": [ | |
| 1, | |
| 1 | |
| ], | |
| "decoder_norm_types": "rms_norm", | |
| "decoder_qkv_multiscales": [ | |
| [], | |
| [ | |
| 5 | |
| ] | |
| ], | |
| "downsample_block_type": "conv", | |
| "encoder_block_out_channels": [ | |
| 8, | |
| 8 | |
| ], | |
| "encoder_block_types": [ | |
| "ResBlock", | |
| "EfficientViTBlock" | |
| ], | |
| "encoder_layers_per_block": [ | |
| 1, | |
| 1 | |
| ], | |
| "encoder_qkv_multiscales": [ | |
| [], | |
| [ | |
| 5 | |
| ] | |
| ], | |
| "in_channels": 3, | |
| "latent_channels": 4, | |
| "scaling_factor": 0.41407, | |
| "upsample_block_type": "interpolate" | |
| } | |