Add application file

app.py

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+import streamlit as st
+from transformers import AutoModelForCausalLM, AutoTokenizer
+import torch
+
+# Load your model and tokenizer from Hugging Face
+model_name = "praty7717/Odeyssey"  # Your Hugging Face repo name
+tokenizer = AutoTokenizer.from_pretrained(model_name)
+m = AutoModelForCausalLM.from_pretrained(model_name)
+
+# Function to generate text from a prompt
+def generate_text(model, prompt, max_length=100):
+    input_ids = tokenizer.encode(prompt, return_tensors="pt")
+    
+    # Generate the output
+    with torch.no_grad():
+        output = model.generate(input_ids, max_length=max_length, num_return_sequences=1)
+    
+    # Decode the generated text
+    generated_text = tokenizer.decode(output[0], skip_special_tokens=True)
+    return generated_text
+
+# Streamlit interface
+st.title("Odeyssey: Poetic Generator")
+st.write("Enter a prompt to generate poetry:")
+
+# Input prompt field
+prompt = st.text_input("Prompt:", value="Once upon a time")  # Default start prompt
+
+# Button to trigger text generation
+if st.button("Generate"):
+    if prompt:
+        # Generate text using the model
+        generated_text = generate_text(m, prompt, max_length=100)
+        
+        # Display the generated text
+        st.subheader("Generated Text:")
+        st.write(generated_text)
+    else:
+       

requirements.txt

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+streamlit
+torch
+transformers