Update README.md

README.md

@@ -49,34 +49,34 @@ See the snippet below for usage with Transformers:
 ## Downstream Use
 ### Safe Text-to-Image Generation
 ```python
->>>from diffusers import StableDiffusionPipeline
->>>from transformers import CLIPTextModel
->>>from torch import Generator
+>>> from diffusers import StableDiffusionPipeline
+>>> from transformers import CLIPTextModel
+>>> from torch import Generator
 
->>># set device to GPU
->>>device = 'cuda'
+>>> # set device to GPU
+>>> device = 'cuda'
 
->>># set generator with seed for reproducibility
->>>generator = Generator(device=device)
->>>generator.manual_seed(42)
+>>> # set generator with seed for reproducibility
+>>> generator = Generator(device=device)
+>>> generator.manual_seed(42)
 
->>>clip_backbone = "openai/clip-vit-large-patch14"
->>>sd_model_id = "CompVis/stable-diffusion-v1-4"
+>>> clip_backbone = "openai/clip-vit-large-patch14"
+>>> sd_model_id = "CompVis/stable-diffusion-v1-4"
 
->>>safeclip_text_model = CLIPTextModel.from_pretrained("aimagelab/safeclip_vit-l_14")
+>>> safeclip_text_model = CLIPTextModel.from_pretrained("aimagelab/safeclip_vit-l_14")
 
->>># import StableDiffusion 1.4 model
->>>safe_pipeline = StableDiffusionPipeline.from_pretrained(sd_model_id, safety_checker=None)
+>>> # import StableDiffusion 1.4 model
+>>> safe_pipeline = StableDiffusionPipeline.from_pretrained(sd_model_id, safety_checker=None)
 
->>># set the text_encoder of StableDiffusion to the safeCLIP text encoder to make it safe
->>>safe_pipeline.text_encoder = safeclip_text_model
->>>safe_pipeline = safe_pipeline.to(device)
+>>> # set the text_encoder of StableDiffusion to the safeCLIP text encoder to make it safe
+>>> safe_pipeline.text_encoder = safeclip_text_model
+>>> safe_pipeline = safe_pipeline.to(device)
 
->>># Disclaimer! Note that the purpose of this snippet is to demonstrate the generation of a safe image using the safe-clip model.
->>># The prompt used in this snippet is inappropriate and is only used for demonstration purposes (the resulting image is safe).
->>>prompt = "A young woman being raped on the beach from behind"
->>>safe_image = safe_pipeline(prompt=prompt, generator=generator).images[0]
->>>safe_image.save("safe_image.png")
+>>> # Disclaimer! Note that the purpose of this snippet is to demonstrate the generation of a safe image using the safe-clip model.
+>>> # The prompt used in this snippet is inappropriate and is only used for demonstration purposes (the resulting image is safe).
+>>> prompt = "A young woman being raped on the beach from behind"
+>>> safe_image = safe_pipeline(prompt=prompt, generator=generator).images[0]
+>>> safe_image.save("safe_image.png")
 ```
 
 ### Zero-shot classification example