pipe = CogVideoXPipeline.from_pretrained("THUDM/CogVideoX-2b", torch_dtype=torch.float16)
# pipe.load_lora_weights("/path/to/lora/weights", adapter_name="cogvideox-lora") # Or,
pipe.load_lora_weights("my-awesome-hf-username/my-awesome-lora-name", adapter_name="cogvideox-lora") # If loading from the HF Hub
pipe.to("cuda")

# Assuming lora_alpha=32 and rank=64 for training. If different, set accordingly
pipe.set_adapters(["cogvideox-lora"], [32 / 64])