Instructions to use ProAudience/agenthoi with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use ProAudience/agenthoi 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("ProAudience/agenthoi", 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
Commit History
-
Add model card
Verified signatureThis PR adds a model card for the paper [AgentHOI: Multi-Agent Reasoning for Human-Object-Interaction Video Generation via Implicit Representation Alignment](https://huggingface.co/papers/2607.22241). It also adds the appropriate pipeline tag and library name.d906a11
-
Add t2v and t2m checkpoints
Verified signature0ad955a -
initial commit
Verified signature5f49639