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
Add pipeline tag, library name and link to project page
#1
by nielsr HF Staff - opened
This PR improves the model card, by:
- Adding the
pipeline_tag: image-to-videometadata, ensuring the model can be found at https://huggingface.co/models?pipeline_tag=image-to-video - Adding the
library_name, ensuring the "how to use" button shows up - Adding a link to the project page