Instructions to use hf-internal-testing/tiny-ShapEPipeline with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use hf-internal-testing/tiny-ShapEPipeline 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-ShapEPipeline", 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
| { | |
| "_class_name": "ShapERenderer", | |
| "_diffusers_version": "0.39.0.dev0", | |
| "act_fn": "swish", | |
| "background": [ | |
| 0.1, | |
| 0.1, | |
| 0.1 | |
| ], | |
| "d_hidden": 8, | |
| "d_latent": 16, | |
| "insert_direction_at": 4, | |
| "n_hidden_layers": 6, | |
| "n_output": 12, | |
| "param_names": [ | |
| "nerstf.mlp.0.weight", | |
| "nerstf.mlp.1.weight", | |
| "nerstf.mlp.2.weight", | |
| "nerstf.mlp.3.weight" | |
| ], | |
| "param_shapes": [ | |
| [ | |
| 8, | |
| 93 | |
| ], | |
| [ | |
| 8, | |
| 8 | |
| ], | |
| [ | |
| 8, | |
| 8 | |
| ], | |
| [ | |
| 8, | |
| 8 | |
| ] | |
| ] | |
| } | |