Image-to-Video
Diffusers
world-model
robotics
teleoperation
video-generation
egocentric
diffusion
causal
streaming
real-time
Instructions to use Alibaba-DAMO-Academy/RynnWorld-Teleop-Causal with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Alibaba-DAMO-Academy/RynnWorld-Teleop-Causal 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("Alibaba-DAMO-Academy/RynnWorld-Teleop-Causal", 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
Download ema_weights.bin from Alibaba-DAMO-Academy/RynnWorld-Teleop-Causal: direct link, hf CLI and curl.
- Browser
- Download file 12.3 GB
-
https://huggingface.co/Alibaba-DAMO-Academy/RynnWorld-Teleop-Causal/resolve/main/ema_weights.bin
- Command line
-
hf download hf://Alibaba-DAMO-Academy/RynnWorld-Teleop-Causal/ema_weights.bin
-
curl -L -o ema_weights.bin https://huggingface.co/Alibaba-DAMO-Academy/RynnWorld-Teleop-Causal/resolve/main/ema_weights.bin
12.3 GB
- Xet hash:
- 9ec2e16dbdaf8f52006b1bf65aff1059aa15b4ba116440300a744dd65056a8f6
- Size of remote file:
- 12.3 GB
- SHA256:
- 605c9e8c717a86f2360f4a092706eff859dc068e73fa5e17a54ebaabfaa4d406
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