Create app.py

app.py

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+# Import required libraries
+import gradio as gr
+from transformers import AutoModelForCausalLM, AutoTokenizer
+
+# Load the model and tokenizer
+MODEL_NAME = "SeaLLMs/SeaLLM-7B-v2.5"
+
+# Download model and tokenizer from Hugging Face
+tokenizer = AutoTokenizer.from_pretrained(MODEL_NAME)
+model = AutoModelForCausalLM.from_pretrained(MODEL_NAME, torch_dtype="auto", device_map="auto")
+
+# Define the chatbot function
+def chatbot(user_input):
+    inputs = tokenizer(user_input, return_tensors="pt").to("cuda")
+    outputs = model.generate(inputs["input_ids"], max_length=150, num_return_sequences=1, temperature=0.7)
+    response = tokenizer.decode(outputs[0], skip_special_tokens=True)
+    return response
+
+# Create a Gradio interface
+interface = gr.Interface(
+    fn=chatbot,
+    inputs="text",
+    outputs="text",
+    title="SeaLLM Chatbot",
+    description="A chatbot powered by SeaLLM-7B-v2.5.",
+    examples=["Hello!", "What's the weather today?", "Tell me a joke!"],
+)
+
+# Launch the interface
+if __name__ == "__main__":
+    interface.launch()