Update app.py

app.py

@@ -1,24 +1,27 @@
-import gradio as gr
+import streamlit as st
 from transformers import AutoTokenizer, AutoModelForCausalLM
+import torch
 
-# Load the model and tokenizer
+# Set up the Hugging Face API token
+HF_token = "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"
+
+# Load the tokenizer and model
 model_name = "Qwen/Qwen1.5-7B"
-tokenizer = AutoTokenizer.from_pretrained(model_name)
-model = AutoModelForCausalLM.from_pretrained(model_name)
+tokenizer = AutoTokenizer.from_pretrained(model_name, use_auth_token=HF_token)
+model = AutoModelForCausalLM.from_pretrained(model_name, use_auth_token=HF_token)
 
+# Function to generate article
 def generate_article(topic):
     inputs = tokenizer(f"Generate article for the NY times tweet {topic}", return_tensors="pt")
     outputs = model.generate(inputs['input_ids'], max_new_tokens=512, temperature=0.5)
     return tokenizer.decode(outputs[0], skip_special_tokens=True)
 
-# Create the Gradio interface
-iface = gr.Interface(
-    fn=generate_article,
-    inputs="text",
-    outputs="text",
-    title="Article Generator",
-    description="Generate an article for a given topic."
-)
-
-# Launch the Gradio app
-iface.launch()
+# Streamlit app interface
+st.title("Article Generator")
+topic = st.text_input("Enter a topic:")
+if st.button("Generate"):
+    if topic:
+        article = generate_article(topic)
+        st.write(article)
+    else:
+        st.write("Please enter a topic.")