initial commit with phi-3 mini

app.py

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+import gradio as gr
+from transformers import AutoTokenizer, AutoModelForCausalLM, pipeline
+
+# Load Phi-3 Mini model
+model_id = "microsoft/phi-3-mini-4k-instruct"
+tokenizer = AutoTokenizer.from_pretrained(model_id)
+model = AutoModelForCausalLM.from_pretrained(model_id, torch_dtype="auto", device_map="auto")
+
+# Pipeline for text generation
+pipe = pipeline("text-generation", model=model, tokenizer=tokenizer)
+
+# Chat function with history
+def chat_fn(message, history):
+    history_text = ""
+    for user, bot in history:
+        history_text += f"<|user|>\n{user}\n<|assistant|>\n{bot}\n"
+    prompt = f"{history_text}<|user|>\n{message}\n<|assistant|>\n"
+    response = pipe(prompt, max_new_tokens=512, do_sample=True, temperature=0.7)[0]['generated_text']
+    reply = response.split("<|assistant|>")[-1].strip()
+    return reply
+
+# Create Chat Interface with authentication and style
+chat = gr.ChatInterface(
+    fn=chat_fn,
+    title="💬 Chat with Phi-3 Mini",
+    description="A lightweight ChatGPT-like assistant powered by Microsoft's Phi-3 Mini. Feel free to ask questions or code!",
+    theme="soft",  # Light elegant theme
+    examples=["What is Python?", "Write a Python function to reverse a list.", "How does an LLM work?"],
+    auth=[("user", "pass")],  # Replace with secure creds in real use
+    additional_inputs=[],
+    submit_btn="Send",
+    retry_btn="↻ Retry",
+    undo_btn="⤺ Undo",
+    clear_btn="🧹 Clear Chat"
+)
+
+chat.launch()

requirements.txt

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+transformers
+gradio
+torch
+accelerate