Qwen-2.5-72B on serverless inference
Communicate with a multimodal chatbot
Generate text responses in a chat interface
Send messages to a WhatsApp-style chatbot
Interact with multiple chatbots simultaneously
Chat with an AI that understands images and text
Display chatbot leaderboard and stats
Interact with NCTC OSINT Agent for OSINT tasks
Example on using Langfuse to trace Gradio applications.
Meta-Llama-3.1-8B-Instruct
Engage in conversations with a multilingual language model
Generate detailed, refined responses to user queries
Marin kitagawa an AI chatbot
Qwen-2.5-72B-Instruct is a chatbot model based on the Qwen-2.5-72B architecture, specifically optimized for serverless inference. It is designed to engage in natural-sounding conversations while focusing on instruction-following tasks. The model is part of the Qwen series, which emphasizes accuracy and performance in generating human-like text responses.
What is the primary use case for Qwen-2.5-72B-Instruct?
Qwen-2.5-72B-Instruct is primarily designed for instruction-following tasks, such as answering questions, generating text, or executing multi-step tasks.
Is Qwen-2.5-72B-Instruct available for local deployment?
No, Qwen-2.5-72B-Instruct is optimized for serverless inference and is typically accessed through cloud-based platforms or APIs.
Does Qwen-2.5-72B-Instruct support multiple languages?
Yes, Qwen-2.5-72B-Instruct has multilingual capabilities, allowing it to understand and respond in multiple languages.