Instructions to use KlingTeam/RoboMaster with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use KlingTeam/RoboMaster with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("KlingTeam/RoboMaster", 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
import torch
from diffusers import DiffusionPipeline
# switch to "mps" for apple devices
pipe = DiffusionPipeline.from_pretrained("KlingTeam/RoboMaster", dtype=torch.bfloat16, device_map="cuda")
prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k"
image = pipe(prompt).images[0]RoboMaster
It synthesizes realistic robotic manipulation video given an initial frame, a prompt, a user-defined object mask, and a collaborative trajectory describing the motion of both robotic arm and manipulated object in decomposed interaction phases. It supports diverse manipulation skills and can generalize to in-the-wild scenarios.
Usage
This is the implementation based on CogVideoX-5B. Please refer to our github for details on usage.
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