python code added

app.py

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+import gradio as gr
+from transformers import AutoTokenizer, AutoModelForCausalLM
+import torch
+
+# Loading Llama model
+model_name = "meta-llama/Llama-2-7b-hf"
+tokenizer = AutoTokenizer.from_pretrained(model_name)
+model = AutoModelForCausalLM.from_pretrained(
+    model_name, device_map="auto", torch_dtype=torch.float16
+)
+
+# Answer generation
+def generate_response(prompt):
+    inputs = tokenizer(prompt, return_tensors="pt").to("cuda")
+    outputs = model.generate(inputs.input_ids, max_length=200, temperature=0.7)
+    return tokenizer.decode(outputs[0], skip_special_tokens=True)
+
+# Gradio interface
+demo = gr.Interface(
+    fn=generate_response,
+    inputs="text",
+    outputs="text",
+    title="Llama Chatbot",
+    description="Chatbot Llama-2-7b-hf",
+)
+
+if __name__ == "__main__":
+    demo.launch()

requirements.txt

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+transformers
+torch
+gradio