Update 01_introduction_to_diffusers.ipynb

Author: tolgacangoz

unit1/01_introduction_to_diffusers.ipynb

@@ -664,7 +664,7 @@
     "\n",
     "Our plan for training is to take these input images and add noise to them, then feed the noisy images to the model. And during inference, we will use the model predictions to iteratively remove noise. In `diffusers`,  these processes are both handled by the **scheduler**. \n",
     "\n",
-    "The noise schedule determines how much noise is added at different timesteps. Here's how we might create a scheduler using the default settings for 'DDPM' training and sampling (based on the paper [\"Denoising Diffusion Probabilistic Models\"](https://arxiv.org/abs/2006.11239):"
+    "The noise schedule determines how much noise is added at different timesteps. Here's how we might create a scheduler using the default settings for 'DDPM' training and sampling (based on the paper [\"Denoising Diffusion Probabilistic Models\"](https://arxiv.org/abs/2006.11239)):"
    ]
   },
   {