Image-to-Video
Diffusers
Safetensors
MOVA
image-text-to-video
image-to-audio-video
image-text-to-audio-video
MOVA
OpenMOSS
SII
MOSI
sglang-diffusion
Instructions to use OpenMOSS-Team/MOVA-360p with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use OpenMOSS-Team/MOVA-360p with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline from diffusers.utils import load_image, export_to_video # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("OpenMOSS-Team/MOVA-360p", dtype=torch.bfloat16, device_map="cuda") pipe.to("cuda") prompt = "A man with short gray hair plays a red electric guitar." image = load_image( "https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/diffusers/guitar-man.png" ) output = pipe(image=image, prompt=prompt).frames[0] export_to_video(output, "output.mp4") - Notebooks
- Google Colab
- Kaggle
| { | |
| "_class_name": "FlowMatchPairScheduler", | |
| "_diffusers_version": "0.36.0", | |
| "exponential_shift": false, | |
| "exponential_shift_mu": null, | |
| "extra_one_step": true, | |
| "inverse_timesteps": false, | |
| "num_inference_steps": 100, | |
| "num_train_timesteps": 1000, | |
| "reverse_sigmas": false, | |
| "shift": 5, | |
| "shift_terminal": null, | |
| "sigma_max": 1.0, | |
| "sigma_min": 0.0 | |
| } | |