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: 493 Bytes
9844c5d | 1 2 3 4 5 6 7 8 9 10 11 | {
"lingbot_video_repo": "https://github.com/Robbyant/lingbot-video",
"lingbot_video_revision": "a2bb04b78edd848500dc27a26e035a95442ae186",
"sdnq_describe": "v0.2.1-17-gd841c38",
"sdnq_repo": "https://github.com/Disty0/sdnq",
"sdnq_revision": "d841c383ff7be38728d4df829e17af4f15d4fd66",
"source_repo_id": "robbyant/lingbot-video-dense-1.3b",
"source_revision": "f9789a7d9b4772a47aba62d4eb5282ddefd1da21",
"target_repo_id": "WaveCut/LingBot-Video-Dense-1.3B-SDNQ-uint4-static"
}
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