Create falco_180b_gradio.py

falco_180b_gradio.py

@@ -0,0 +1,23 @@
+# falcon_180b_gradio.py
+
+import gradio as gr
+from transformers import AutoModelForCausalLM, AutoTokenizer
+
+def main():
+    # Load the model and tokenizer
+    model_name = "bigscience/falcon-180b"  # Replace with the correct model name if different
+    tokenizer = AutoTokenizer.from_pretrained(model_name)
+    model = AutoModelForCausalLM.from_pretrained(model_name)
+
+    # Define the function that uses the model
+    def generate_text(input_text):
+        inputs = tokenizer(input_text, return_tensors="pt", max_length=512, truncation=True)
+        outputs = model.generate(**inputs, max_length=512, min_length=50, num_return_sequences=1)
+        return tokenizer.decode(outputs[0], skip_special_tokens=True)
+
+    # Create and launch the Gradio interface
+    iface = gr.Interface(fn=generate_text, inputs="text", outputs="text", title="Falcon 180B Text Generator")
+    iface.launch()
+
+if __name__ == "__main__":
+    main()