Instructions to use optimum-intel-internal-testing/tiny-stable-diffusion-torch with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use optimum-intel-internal-testing/tiny-stable-diffusion-torch with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("optimum-intel-internal-testing/tiny-stable-diffusion-torch", 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
IlyasMoutawwakil HF Staff
Mirror from hf-internal-testing/tiny-stable-diffusion-torch
f935f13 verified | { | |
| "_class_name": "AutoencoderKL", | |
| "_diffusers_version": "0.7.0.dev0", | |
| "act_fn": "silu", | |
| "block_out_channels": [ | |
| 32, | |
| 64 | |
| ], | |
| "down_block_types": [ | |
| "DownEncoderBlock2D", | |
| "DownEncoderBlock2D" | |
| ], | |
| "in_channels": 3, | |
| "latent_channels": 4, | |
| "layers_per_block": 1, | |
| "norm_num_groups": 32, | |
| "out_channels": 3, | |
| "sample_size": 128, | |
| "up_block_types": [ | |
| "UpDecoderBlock2D", | |
| "UpDecoderBlock2D" | |
| ] | |
| } | |