Instructions to use AlayaLab/AlayaWorld with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use AlayaLab/AlayaWorld 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("AlayaLab/AlayaWorld", 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 modular_model_index.json from AlayaLab/AlayaWorld: direct link, hf CLI and curl.
- Browser
- Download file 297 Bytes
-
https://huggingface.co/AlayaLab/AlayaWorld/resolve/main/modular_model_index.json
- Command line
-
hf download hf://AlayaLab/AlayaWorld/modular_model_index.json
-
curl -L -o modular_model_index.json https://huggingface.co/AlayaLab/AlayaWorld/resolve/main/modular_model_index.json
297 Bytes
| { | |
| "_class_name": "AlayaWorldPipeline", | |
| "model_type": "alayaworld", | |
| "version": "v1.0", | |
| "components": { | |
| "merged_infer": ["merged_infer.safetensors", "DiT + VAE + text encoder + history encoder, single-file inference bundle"] | |
| }, | |
| "homepage": "https://github.com/AlayaLab/AlayaWorld" | |
| } | |