Upload app.py

app.py

@@ -0,0 +1,95 @@
+import os
+from threading import Thread
+import gradio as gr
+import torch
+from transformers import AutoModelForCausalLM, AutoTokenizer, TextIteratorStreamer
+
+MODEL_ID = "clem/macron-style-qwen2.5-1.5B"
+
+try:
+    import spaces
+    HAS_SPACES = True
+except ImportError:
+    HAS_SPACES = False
+
+tokenizer = AutoTokenizer.from_pretrained(MODEL_ID)
+model = AutoModelForCausalLM.from_pretrained(
+    MODEL_ID,
+    torch_dtype=torch.float16 if torch.cuda.is_available() else torch.float32,
+    device_map="auto",
+    use_cache=True,
+)
+
+
+def _generate(input_ids, max_new_tokens, temperature, top_p):
+    streamer = TextIteratorStreamer(
+        tokenizer, timeout=30.0, skip_prompt=True, skip_special_tokens=True
+    )
+    generate_kwargs = dict(
+        input_ids=input_ids.to(model.device),
+        streamer=streamer,
+        max_new_tokens=max_new_tokens,
+        do_sample=True,
+        temperature=temperature,
+        top_p=top_p,
+        eos_token_id=tokenizer.eos_token_id,
+    )
+    Thread(target=model.generate, kwargs=generate_kwargs, daemon=True).start()
+    output = ""
+    for chunk in streamer:
+        output += chunk
+        yield output
+
+
+if HAS_SPACES:
+    _generate = spaces.GPU(_generate)
+
+
+def respond(
+    message: str,
+    chat_history: list[dict],
+    system_prompt: str,
+    max_new_tokens: int,
+    temperature: float,
+    top_p: float,
+):
+    conversation = []
+    if system_prompt.strip():
+        conversation.append({"role": "system", "content": system_prompt})
+    conversation.extend(chat_history)
+    conversation.append({"role": "user", "content": message})
+
+    input_ids = tokenizer.apply_chat_template(
+        conversation,
+        add_generation_prompt=True,
+        return_tensors="pt",
+    )
+    yield from _generate(input_ids, max_new_tokens, temperature, top_p)
+
+
+demo = gr.ChatInterface(
+    fn=respond,
+    type="messages",
+    chatbot=gr.Chatbot(height=500, type="messages"),
+    additional_inputs=[
+        gr.Textbox(
+            value="You are Emmanuel Macron, President of the French Republic. Respond in his characteristic style: eloquent, diplomatic yet direct, reformist, and deeply European.",
+            label="System prompt",
+            lines=3,
+        ),
+        gr.Slider(64, 1024, value=256, step=64, label="Max new tokens"),
+        gr.Slider(0.1, 2.0, value=0.7, step=0.1, label="Temperature"),
+        gr.Slider(0.1, 1.0, value=0.95, step=0.05, label="Top-p"),
+    ],
+    examples=[
+        ["What is your vision for Europe?"],
+        ["Comment voyez-vous le rôle de l'IA dans la société ?"],
+        ["How do you respond to critics of your reform agenda?"],
+    ],
+    cache_examples=False,
+    title="💬 Macron-style Qwen2.5-1.5B",
+    description="A Qwen2.5-1.5B fine-tuned to speak in the style of Emmanuel Macron. Trained on [clem/macron-style-conversations](https://hf.co/datasets/clem/macron-style-conversations).",
+)
+
+if __name__ == "__main__":
+    demo.launch()