Update README.md

README.md

@@ -30,7 +30,7 @@ bs = 1
 latents = ... # maybe some latent codes of real images or SD generation
 latent_mean = latent.mean(dim=0)
 init_latent = latent_mean.repeat(bs,1,1,1) + latents.std()*torch.randn_like(latents) 
-noise = torch.randn([1,bs,64,64])
+noise = torch.randn([bs,4,64,64])
 input_latent = pipeline.scheduler.add_noise(init_latent,noise,T)
 imgs= pipeline(prompt="A photo of a dog",
                     num_inference_steps=steps,