Qwen-2.5-72B on serverless inference
Engage in chat conversations
Vision Chatbot with ImgGen & Web Search - Runs on CPU
Generate text chat conversations using images and text prompts
Generate chat responses from user input
Engage in conversations with a multilingual language model
Generate detailed step-by-step answers to questions
Engage in intelligent chats using the NCTC OSINT AGENT
Chat with an empathetic dialogue system
Interact with an AI therapist that analyzes text and voice emotions, and responds with text-to-speech
Generate conversational responses to text input
Compare chat responses from multiple models
Interact with a chatbot that searches for information and reasons based on your queries
Qwen-2.5-72B-Instruct is a large language model designed for conversational interactions. It is based on the Qwen-2.5 architecture, scaled up to 72 billion parameters, and optimized for instruction-following tasks. The model is deployed using serverless inference, enabling efficient and scalable interactions through a chat interface.
What makes Qwen-2.5-72B-Instruct different from other models?
Qwen-2.5-72B-Instruct is optimized for instruction-following tasks and leverages serverless architecture for efficient deployment, making it both versatile and scalable.
Can I use Qwen-2.5-72B-Instruct for commercial purposes?
Yes, the model supports commercial use cases, including customer service, content generation, and more, subject to the terms of service.
Do I need special hardware to run Qwen-2.5-72B-Instruct?
No, the model is designed for serverless inference, meaning you can access it without needing dedicated hardware or complex setup.