Instructions to use Kry4ta1/Effecteraser-VOR-Inference with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Kry4ta1/Effecteraser-VOR-Inference with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("Kry4ta1/Effecteraser-VOR-Inference", 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
Download checkpoints/dmd_2step/config.json from Kry4ta1/Effecteraser-VOR-Inference: direct link, hf CLI and curl.
- Browser
- Download file 605 Bytes
-
https://huggingface.co/Kry4ta1/Effecteraser-VOR-Inference/resolve/main/checkpoints/dmd_2step/config.json
- Command line
-
hf download hf://Kry4ta1/Effecteraser-VOR-Inference/checkpoints/dmd_2step/config.json
-
curl -L -o config.json https://huggingface.co/Kry4ta1/Effecteraser-VOR-Inference/resolve/main/checkpoints/dmd_2step/config.json
605 Bytes
| { | |
| "_class_name": "VaceWanModel", | |
| "_diffusers_version": "0.34.0", | |
| "cross_attn_norm": true, | |
| "dim": 1536, | |
| "eps": 1e-06, | |
| "ffn_dim": 8960, | |
| "freq_dim": 256, | |
| "hidden_size": 1536, | |
| "in_channels": 16, | |
| "in_dim": 16, | |
| "model_type": "vace", | |
| "num_heads": 12, | |
| "num_layers": 30, | |
| "out_dim": 16, | |
| "patch_size": [ | |
| 1, | |
| 2, | |
| 2 | |
| ], | |
| "qk_norm": true, | |
| "text_dim": 4096, | |
| "text_len": 512, | |
| "vace_in_dim": 96, | |
| "vace_layers": [ | |
| 0, | |
| 2, | |
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| ], | |
| "window_size": [ | |
| -1, | |
| -1 | |
| ] | |
| } | |