Create app.py

app.py

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+import gradio as gr
+from transformers import pipeline, set_seed
+
+# Load the h2oai/h2ogpt-oasst1-512-20b model from Hugging Face
+generator = pipeline('text-generation', model='h2oai/h2ogpt-oasst1-512-20b', device=0)
+
+# Set the seed for the model to ensure consistent results
+set_seed(42)
+
+# Define the chatbot function
+def chatbot(input_text):
+    # Generate a response from the model given the input text
+    output_text = generator(input_text, max_length=100)[0]['generated_text']
+    # Return the generated response
+    return output_text.strip()
+
+# Create a Gradio interface for the chatbot
+interface = gr.Interface(
+    fn=chatbot, 
+    inputs=gr.inputs.Textbox(lines=2, label="Input Text"), 
+    outputs=gr.outputs.Textbox(label="Generated Text")
+)
+
+# Launch the interface
+interface.launch()