Instructions to use Shriramnag/Shiv-AI-Video-Generator with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Shriramnag/Shiv-AI-Video-Generator with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("Shriramnag/Shiv-AI-Video-Generator", 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: 501 Bytes
b23071f | 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 | {
"_class_name": "AutoencoderKLLTXVideo",
"_diffusers_version": "0.32.0.dev0",
"block_out_channels": [
128,
256,
512,
512
],
"decoder_causal": false,
"encoder_causal": true,
"in_channels": 3,
"latent_channels": 128,
"layers_per_block": [
4,
3,
3,
3,
4
],
"out_channels": 3,
"patch_size": 4,
"patch_size_t": 1,
"resnet_norm_eps": 1e-06,
"scaling_factor": 1.0,
"spatio_temporal_scaling": [
true,
true,
true,
false
]
} |