satablediffusion-2-1

app.py

@@ -1,10 +1,30 @@
+# import streamlit as st
+# from transformers import pipeline
+
+# pipe = pipeline('sentiment-analysis')
+# text= st.text_area('enter some text')
+
+# if st.button('Submit'):
+#     if text:
+#         out = pipe(text)
+#         st.write(out)
 import streamlit as st
-from transformers import pipeline
+from transformers import AutoModelForImageGeneration, AutoTokenizer
+from PIL import Image
+import torch
+
+model_name = "stabilityai/stable-diffusion-2-1" # loading the model
+model = AutoModelForImageGeneration.from_pretrained(model_name)
+tokenizer = AutoTokenizer.from_pretrained(model_name)
+
+text_input = st.text_area('Enter some text') #getting user text
 
-pipe = pipeline('sentiment-analysis')
-text= st.text_area('enter some text')
+if st.button('Generate Image'):
+    if text_input:
+        input_ids = tokenizer(text_input, return_tensors="pt").input_ids #input token
+        with torch.no_grad(): #img generation
+            output = model.generate(input_ids)
+            
+        image = Image.fromarray(output[0].numpy().astype('uint8')) # certing tensor to imgonv
 
-if st.button('Submit'):
-    if text:
-        out = pipe(text)
-        st.write(out)
+        st.image(image, caption='Generated Image', use_column_width=True) #display output