Instructions to use zai-org/CogVideoX1.5-5B-I2V with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use zai-org/CogVideoX1.5-5B-I2V 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("zai-org/CogVideoX1.5-5B-I2V", 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
conv3d error
#11
by lgao-metax - opened
RuntimeError: Calculated padded input size per channel: (1 x 2402 x 2402). Kernel size: (3 x 3 x 3). Kernel size can't be greater than actual input size
Were you able to find the solution for this?
They have no this code in gradio demo(github):
pipe.vae.enable_tiling()
pipe.vae.enable_slicing()
Adding the above code can solve the problem.
lgao-metax changed discussion status to closed