Instructions to use optimum-intel-internal-testing/tiny-random-z-image with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use optimum-intel-internal-testing/tiny-random-z-image 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-random-z-image", 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 Settings
- Draw Things
- DiffusionBee
Download transformer/config.json from optimum-intel-internal-testing/tiny-random-z-image: direct link, hf CLI and curl.
- Browser
- Download file 487 Bytes
-
https://huggingface.co/optimum-intel-internal-testing/tiny-random-z-image/resolve/main/transformer/config.json
- Command line
-
hf download hf://optimum-intel-internal-testing/tiny-random-z-image/transformer/config.json
-
curl -L -o config.json https://huggingface.co/optimum-intel-internal-testing/tiny-random-z-image/resolve/main/transformer/config.json
487 Bytes
| { | |
| "_class_name": "ZImageTransformer2DModel", | |
| "_diffusers_version": "0.39.0", | |
| "all_f_patch_size": [ | |
| 1 | |
| ], | |
| "all_patch_size": [ | |
| 2 | |
| ], | |
| "axes_dims": [ | |
| 8, | |
| 12, | |
| 12 | |
| ], | |
| "axes_lens": [ | |
| 1536, | |
| 512, | |
| 512 | |
| ], | |
| "cap_feat_dim": 32, | |
| "dim": 64, | |
| "in_channels": 16, | |
| "n_heads": 2, | |
| "n_kv_heads": 2, | |
| "n_layers": 2, | |
| "n_refiner_layers": 2, | |
| "norm_eps": 1e-05, | |
| "qk_norm": true, | |
| "rope_theta": 256.0, | |
| "siglip_feat_dim": null, | |
| "t_scale": 1000.0 | |
| } | |