Instructions to use hf-internal-testing/tiny-LTX2Pipeline with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use hf-internal-testing/tiny-LTX2Pipeline 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-LTX2Pipeline", 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
File size: 555 Bytes
f0dc9e2 | 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 30 31 32 33 34 | {
"_class_name": "LTX2Vocoder",
"_diffusers_version": "0.39.0.dev0",
"act_fn": "leaky_relu",
"antialias": false,
"antialias_kernel_size": 12,
"antialias_ratio": 2,
"final_act_fn": "tanh",
"final_bias": true,
"hidden_channels": 32,
"in_channels": 16,
"leaky_relu_negative_slope": 0.1,
"out_channels": 2,
"output_sampling_rate": 16000,
"resnet_dilations": [
[
1,
3,
5
]
],
"resnet_kernel_sizes": [
3
],
"upsample_factors": [
2,
2
],
"upsample_kernel_sizes": [
4,
4
]
}
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