Instructions to use YiYiXu/taew2_2-diffusers with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use YiYiXu/taew2_2-diffusers with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("YiYiXu/taew2_2-diffusers", dtype=torch.bfloat16, device_map="cuda") prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k" image = pipe(prompt).images[0] - Wan2.2
How to use YiYiXu/taew2_2-diffusers with Wan2.2:
# No code snippets available yet for this library. # To use this model, check the repository files and the library's documentation. # Want to help? PRs adding snippets are welcome at: # https://github.com/huggingface/huggingface.js
- Notebooks
- Google Colab
- Kaggle
File size: 409 Bytes
2b4de06 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 | {
"_class_name": "AutoencoderTinyVideo",
"_diffusers_version": "0.40.0.dev0",
"decoder_block_out_channels": [
256,
128,
64,
64
],
"decoder_time_upscale": [
false,
true,
true
],
"encoder_block_out_channels": [
64,
64,
64
],
"encoder_time_downscale": [
true,
true,
false
],
"in_channels": 3,
"latent_channels": 48,
"patch_size": 2
}
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