Instructions to use WaveCut/LingBot-Video-Dense-1.3B-SDNQ-uint4-static with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use WaveCut/LingBot-Video-Dense-1.3B-SDNQ-uint4-static with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("WaveCut/LingBot-Video-Dense-1.3B-SDNQ-uint4-static", 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: 508 Bytes
9844c5d | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 | {
"_class_name": "LingBotVideoPipeline",
"_diffusers_version": "0.37.1",
"transformer": [
"lingbot_video_diffusers.transformer_lingbot_video",
"LingBotVideoTransformer3DModel"
],
"vae": [
"diffusers",
"AutoencoderKLWan"
],
"text_encoder": [
"transformers",
"Qwen3VLForConditionalGeneration"
],
"processor": [
"transformers",
"Qwen3VLProcessor"
],
"scheduler": [
"lingbot_video_diffusers.scheduling_flow_unipc",
"FlowUniPCMultistepScheduler"
]
} |