Image-to-Video
Diffusers
Safetensors
video-generation
audio-video-generation
reference-to-video
long-video
multi-shot
dmd
Instructions to use jdopensource/JoyAI-Echo with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use jdopensource/JoyAI-Echo 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("jdopensource/JoyAI-Echo", 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 vae/diffusion_pytorch_model.safetensors from jdopensource/JoyAI-Echo: direct link, hf CLI and curl.
- Browser
- Download file 1.45 GB
-
https://huggingface.co/jdopensource/JoyAI-Echo/resolve/main/vae/diffusion_pytorch_model.safetensors
- Command line
-
hf download hf://jdopensource/JoyAI-Echo/vae/diffusion_pytorch_model.safetensors
-
curl -L -o diffusion_pytorch_model.safetensors https://huggingface.co/jdopensource/JoyAI-Echo/resolve/main/vae/diffusion_pytorch_model.safetensors
1.45 GB
- Xet hash:
- 77b782d089ff83b901ed4d3447353e35e15cab200a15205fbf5f33254744182e
- Size of remote file:
- 1.45 GB
- SHA256:
- 425f0dfa227dee5d0ff3d9720563370810409a439c302ca74f0f944057ce55c5
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.