Instructions to use byungjun-kim/DWM-CogVideoX-Fun-5b-LoRA with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use byungjun-kim/DWM-CogVideoX-Fun-5b-LoRA 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("alibaba-pai/CogVideoX-Fun-V1.1-5b-InP", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("byungjun-kim/DWM-CogVideoX-Fun-5b-LoRA") prompt = "A man with short gray hair plays a red electric guitar." input_image = load_image("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/diffusers/guitar-man.png") image = pipe(image=input_image, prompt=prompt).frames[0] export_to_video(output, "output.mp4") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
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