Text-to-Video
Diffusers
Safetensors
English
MotifVideoPipeline
image-to-video
video-generation
diffusion-transformer
Instructions to use Motif-Technologies/Motif-Video-2B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Motif-Technologies/Motif-Video-2B with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("Motif-Technologies/Motif-Video-2B", dtype=torch.bfloat16, device_map="cuda") prompt = "A vibrant blue jay perches gracefully on a slender branch, its feathers shimmering in the soft morning light. The bird's keen eyes scan the surroundings, capturing the essence of the tranquil forest. It flutters its wings briefly, showcasing the intricate patterns of blue, white, and black on its plumage. The background reveals a lush canopy of green leaves, with rays of sunlight filtering through, creating a dappled effect on the forest floor. The blue jay then tilts its head, emitting a melodious call that echoes through the serene woodland, adding a touch of magic to the peaceful scene." image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
Commit History
Delete motif-video-technical-report.pdf 0e8fceb verified
Update README.md 68210f0 verified
Update README.md 82fb28f verified
chore: remove .plans from tracking (internal working docs) c863b63
chore: close low-vram-inference plan (MM-1091) 0ed7f12
feat: enable_model_cpu_offload() for 24GB GPUs + README update 160bda0
Update README.md 8114af8 verified
add-tech-report (#2) 3e1bd47
Update techreport link to Motifvideo_techreport.pdf b8007d8
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