Update README.md

README.md

@@ -10,9 +10,14 @@ from diffusers.utils import export_to_gif
 
 # Load the motion adapter
 adapter = MotionAdapter.from_pretrained("guoyww/animatediff-motion-adapter-v1-5-2", torch_dtype=torch.float16)
-# load SD 1.5 based finetuned model
+
+# Load SD 1.5 based finetuned model
 model_id = "zecloud/mechas"
-pipe = AnimateDiffPipeline.from_pretrained(model_id, motion_adapter=adapter, torch_dtype=torch.float16)
+pipe = AnimateDiffPipeline.from_pretrained(
+    model_id,
+    motion_adapter=adapter,
+    torch_dtype=torch.float16
+)
 scheduler = DDIMScheduler.from_pretrained(
     model_id,
     subfolder="scheduler",
@@ -23,19 +28,27 @@ scheduler = DDIMScheduler.from_pretrained(
 )
 pipe.scheduler = scheduler
 
-# enable memory savings
+# Enable memory savings
 pipe.enable_vae_slicing()
 pipe.enable_model_cpu_offload()
 
+# Define the input prompts and generate the output
 output = pipe(
     prompt=(
-         "half body portrait of man smiling with a mysterious gaze, mecha, science_fiction, city, realistic,mecha, a futuristic eiffel tower in the background "
+        "half body portrait of man smiling with a mysterious gaze, mecha, science_fiction, city, realistic,mecha, "
+        "a futuristic eiffel tower in the background "
+    ),
+    negative_prompt=(
+        "(worst quality, low quality:1.4), (bad_prompt_version2:0.8), EasyNegative, badhandv4, text, name, letters, "
+        "watermark, two tower"
     ),
-    negative_prompt="(worst quality, low quality:1.4), (bad_prompt_version2:0.8), EasyNegative, badhandv4, text, name, letters, watermark, two tower",
     num_frames=16,
     guidance_scale=7.0,
     num_inference_steps=32,
     generator=torch.Generator("cpu").manual_seed(42),
 )
+
+# Extract frames and export to GIF
 frames = output.frames[0]
 export_to_gif(frames, "animation.gif")
+