Create app.py

app.py

@@ -0,0 +1,25 @@
+import streamlit as st
+from transformers import AutoTokenizer, AutoModelForCausalLM
+
+# Load the model and tokenizer
+@st.cache_resource
+def load_model():
+    tokenizer = AutoTokenizer.from_pretrained("Qwen/Qwen-7B")
+    model = AutoModelForCausalLM.from_pretrained("Qwen/Qwen-7B")
+    return tokenizer, model
+
+tokenizer, model = load_model()
+
+# Streamlit app UI
+st.title("Qwen-7B Text Generation")
+
+# Text input
+user_input = st.text_area("Enter your text:")
+
+# Generate text on button click
+if st.button("Generate"):
+    inputs = tokenizer(user_input, return_tensors="pt")
+    outputs = model.generate(**inputs, max_length=100)
+    generated_text = tokenizer.decode(outputs[0], skip_special_tokens=True)
+    st.write("Generated Text:")
+    st.write(generated_text)