Update app.py

app.py

@@ -42,6 +42,30 @@
 
 
 
+import torch
+from transformers import AutoModelForDiffusion, DiffusionConfig
+
+# Specify the model parameters
+model_config = DiffusionConfig(
+    image_size=64,
+    num_channels=3,
+    num_steps=1000,
+    diffusion_steps=100,
+    noise_schedule="linear",
+    learning_rate=0.0001,
+)
+
+# Load the model
+model = AutoModelForDiffusion.from_pretrained("runwayml/stable-diffusion-v1-5", config=model_config)
+
+# Generate an image
+image = model.generate(text="This is a test")
+
+# Save the image
+torch.save(image, "image.png")
+
+
+
 
 # # Import streamlit and huggingface libraries
 # import streamlit as st
@@ -88,6 +112,25 @@
 
 
 
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 # import streamlit as st
@@ -126,26 +169,26 @@
 
 
 
-import streamlit as st
-from transformers import AutoModelForSeq2SeqLM, AutoTokenizer
+# import streamlit as st
+# from transformers import AutoModelForSeq2SeqLM, AutoTokenizer
 
-# Load the text-to-speech model from Huggingface Spaces
-model_id = "facebook/bart-base-tts"
-model = AutoModelForSeq2SeqLM.from_pretrained(model_id)
-tokenizer = AutoTokenizer.from_pretrained(model_id)
+# # Load the text-to-speech model from Huggingface Spaces
+# model_id = "facebook/bart-base-tts"
+# model = AutoModelForSeq2SeqLM.from_pretrained(model_id)
+# tokenizer = AutoTokenizer.from_pretrained(model_id)
 
-# Create a text input field
-text = st.text_input("Enter some text:")
+# # Create a text input field
+# text = st.text_input("Enter some text:")
 
-# If the user enters some text, generate the speech
-if text:
-    # Tokenize the text
-    inputs = tokenizer(text=text, return_tensors="pt")
+# # If the user enters some text, generate the speech
+# if text:
+#     # Tokenize the text
+#     inputs = tokenizer(text=text, return_tensors="pt")
 
-    # Generate the speech
-    generated_speech = model.generate(**inputs)
+#     # Generate the speech
+#     generated_speech = model.generate(**inputs)
 
-    # Play the speech
-    st.audio(generated_speech, format="wav")
+#     # Play the speech
+#     st.audio(generated_speech, format="wav")