Instructions to use hvent90/point_navigation with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use hvent90/point_navigation with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("hvent90/point_navigation", 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
| license: mit | |
| tags: | |
| - pytorch | |
| - diffusers | |
| - conditional-navigation | |
| - diffusion-models-class | |
| # Simple Point Navigation | |
| This generates a path between two points in a 2D grid. Basically AGI. | |
| ## Usage | |
| ```python | |
| from diffusers import DiffusionPipeline | |
| pipeline = DiffusionPipeline.from_pretrained("hvent90/point_navigation", trust_remote_code=True) | |
| trajectory = pipeline(start=[0, 0], target=[0.8, 0.8]).trajectories[0] | |
| print(trajectory) # 32 waypoints from start to target | |
| ``` | |