Create app.py

app.py

@@ -0,0 +1,46 @@
+import gradio as gr
+from transformers import AutoTokenizer, AutoModelForCausalLM
+import argparse
+
+# Load the pre-trained model and tokenizer
+models = {
+    "EleutherAI/gpt-neo-2.7B": "EleutherAI/gpt-neo-2.7B",
+    "BlinkDL/rwkv-4-pile-430m": "BlinkDL/rwkv-4-pile-430m",
+    "BlinkDL/rwkv-4-pile-1b5": "BlinkDL/rwkv-4-pile-1b5",
+    "BlinkDL/RWKV-4-Raven": "BlinkDL/RWKV-4-Raven"
+}
+
+def generate_text(prompt, model_name):
+    tokenizer = AutoTokenizer.from_pretrained(model_name)
+    model = AutoModelForCausalLM.from_pretrained(model_name)
+
+    # Tokenize the input
+    input_ids = tokenizer.encode(prompt, return_tensors="pt")
+
+    # Generate a response
+    output = model.generate(input_ids, max_length=100, num_return_sequences=1)
+
+    # Decode the output
+    generated_text = tokenizer.decode(output[0], skip_special_tokens=True)
+
+    return generated_text
+
+def main():
+    # Create a Gradio interface
+    model_dropdown = gr.inputs.Dropdown(choices=list(models.keys()), label="Select Model")
+    prompt_input = gr.inputs.Textbox(lines=5, placeholder="Enter your prompt here...", label="Prompt")
+    output_text = gr.outputs.Textbox(label="Generated Text")
+
+    interface = gr.Interface(
+        fn=generate_text,
+        inputs=[prompt_input, model_dropdown],
+        outputs=output_text,
+        title="Chat-bot using RWKV LLM",
+        description="Select a model and enter a prompt to generate text using the chat-bot."
+    )
+
+    # Launch the interface
+    interface.launch()
+
+if __name__ == '__main__':
+    main()