Update README.md

README.md

@@ -48,14 +48,14 @@ import torch
 from diffusers import CogVideoXImageToVideoPipeline
 from diffusers.utils import load_image, export_to_video
 
-pipe = CogVideoXImageToVideoPipeline.from_pretrained("THUDM/CogVideoX-5b", torch_dtype=torch.bfloat16).to("cuda")
-pipe.load_lora_weights("BelGio13/cogvideoX-I2V-locobot", weight_name="pytorch_lora_weights.safetensors", adapter_name=["cogvideox-i2v-lora"])
+pipe = CogVideoXImageToVideoPipeline.from_pretrained("THUDM/CogVideoX-5b-I2V", torch_dtype=torch.bfloat16).to("cuda")
+pipe.load_lora_weights("BelGio13/cogvideoX-I2V-locobot", weight_name="pytorch_lora_weights.safetensors", adapter_name="cogvideox-i2v-lora")
 
 # The LoRA adapter weights are determined by what was used for training.
 # In this case, we assume `--lora_alpha` is 32 and `--rank` is 64.
 # It can be made lower or higher from what was used in training to decrease or amplify the effect
 # of the LoRA upto a tolerance, beyond which one might notice no effect at all or overflows.
-pipe.set_adapters(["cogvideox-i2v-lora"], [32 / 64])
+pipe.set_adapters("cogvideox-i2v-lora", [32 / 64])
 
 image = load_image("/path/to/image")
 video = pipe(image=image, "", guidance_scale=6, use_dynamic_cfg=True).frames[0]