Update README.md

README.md

@@ -24,13 +24,24 @@ This pipeline was finetuned from **CompVis/stable-diffusion-v1-4** with replacem
 You can use the pipeline like so:
 
 ```python
-from diffusers import DiffusionPipeline
+from diffusers import StableDiffusionPipeline
 import torch
 
-pipeline = DiffusionPipeline.from_pretrained("jangmin/foodai-pipeline-ko", torch_dtype=torch.float16)
-prompt = "해물 짬뽕"
-image = pipeline(prompt).images[0]
-image.save("my_image.png")
+# Set device
+device = (
+    "mps"
+    if torch.backends.mps.is_available()
+    else "cuda"
+    if torch.cuda.is_available()
+    else "cpu"
+)
+torch_dtype = torch.float16 if device == "cuda" else torch.float32
+pipeline = StableDiffusionPipeline.from_pretrained("jangmin/foodai-pipeline-ko", torch_dtype=torch_dtype)
+pipeline.to(device)
+
+prompt = "짜장면, 정면에서 본 사진, 그릇에 담긴"
+image = pipeline(prompt, guidance_scale=8, num_inference_steps=35).images[0]
+image
 ```
 
 ## Training info
@@ -44,20 +55,3 @@ These are the key hyperparameters used during training:
 * Image resolution:512
 * Mixed-precision: bf16
 
-
-
-## Intended uses & limitations
-
-#### How to use
-
-```python
-# TODO: add an example code snippet for running this diffusion pipeline
-```
-
-#### Limitations and bias
-
-[TODO: provide examples of latent issues and potential remediations]
-
-## Training details
-
-[TODO: describe the data used to train the model]