| from transformers import AutoModelForCausalLM, AutoTokenizer | |
| model_name = "inclusionAI/Ring-mini-2.0" | |
| print(f"load model {model_name}") | |
| model = AutoModelForCausalLM.from_pretrained( | |
| model_name, | |
| torch_dtype="auto", | |
| device_map="auto", | |
| trust_remote_code=True | |
| ) | |
| print(f"load tokenizer {model_name}") | |
| tokenizer = AutoTokenizer.from_pretrained(model_name) | |
| from flask import Flask | |
| app = Flask(__name__) | |
| print(f"Flask app") | |
| # Главная страница | |
| def home(): | |
| return f"<h1>Главная страница</h1><p>Добро пожаловать!</p><p>current model {model_name}</p>" | |
| # Страница "О нас" | |
| def about(): | |
| return "<h1>О нас</h1><p>Мы изучаем Flask!</p>" | |
| # Страница "Контакты" | |
| def contact(): | |
| return "<h1>Контакты</h1><p>Свяжитесь с нами: email@example.com</p>" | |
| if __name__ == "__main__": | |
| app.run(debug=False, host='0.0.0.0', port=7860) |