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We couldn't find any matching results.

Qwen/Qwen2.5-14B-Instruct

Qwen2.5-14B-Instruct is a large language model by Alibaba’s Qwen team, optimized for instruction-following tasks with 14 billion parameters. It offers strong reasoning, multilingual capabilities, and efficient performance, making it suitable for chatbots, content creation, and various AI-driven applications.
Run time: 1 second
1384 runs
0

Qwen/Qwen2.5-32B-Instruct

Qwen2.5-32B-Instruct is a powerful large language model developed by Alibaba’s Qwen team, designed for instruction-following tasks with enhanced reasoning and natural language understanding capabilities. Optimized for efficiency and accuracy, it supports multi-turn conversations and complex queries, making it suitable for applications such as chatbots, content generation, and AI assistants.
Run time: 1 second
1571 runs
0

Qwen/Qwen2.5-3B-Instruct

Qwen/Qwen2.5-3B-Instruct is a powerful 3 billion parameter AI language model designed to deliver high-quality, human-like responses across a wide range of natural language processing tasks.
Run time: 1 second
2623 runs
0

Qwen/Qwen2.5-0.5B-Instruct

Qwen/Qwen2.5-0.5B-Instruct is a compact 500 million parameter AI language model optimized for generating human-like responses and assisting with various natural language understanding tasks.
Run time: 1 second
1305 runs
0

Qwen/Qwen2.5-1.5B-Instruct

Qwen/Qwen2.5-1.5B-Instruct is a 1.5 billion parameter AI language model designed to generate human-like responses based on user inputs.
Run time: 1 second
2778 runs
0

Qwen/Qwen2-7B-Instruct

Qwen2-7B-Instruct is a versatile large language model with 7 billion parameters, optimized for instruction-following tasks. It delivers high performance in natural language understanding, content generation, and complex reasoning, making it ideal for a wide range of AI-driven applications, from chatbots to educational tools.
Run time: 1 second
1400 runs
0

Qwen/Qwen2.5-Math-7B-Instruct

Qwen2.5-Math-7B-Instruct is a large language model with 7 billion parameters, specialized in advanced mathematical problem-solving and reasoning. It is fine-tuned for instruction-based tasks and excels in fields like algebra, calculus, and quantitative analysis, making it suitable for research, education, and technical applications.
Run time: 1 second
1397 runs
0

Qwen/Qwen2.5-Math-1.5B-Instruct

Qwen2.5-Math-1.5B-Instruct is a math-specialized large language model with 1.5 billion parameters, fine-tuned for solving complex mathematical problems and handling instruction-based tasks. It excels in areas like algebra, calculus, and numerical reasoning, making it ideal for educational tools and research applications.
Run time: 1 second
1071 runs
0

Qwen/Qwen2.5-Coder-7B-Instruct

Qwen2.5-Coder-7B-Instruct is a specialized large language model with 7 billion parameters, designed for code understanding and generation. Fine-tuned for instruction-based tasks, it supports multiple programming languages, making it ideal for coding assistance, code completion, and educational applications.
Run time: 1 second
1584 runs
0

Qwen/Qwen1.5-0.5B-Chat

Qwen1.5-0.5B-Chat is a lightweight conversational AI model with 500 million parameters, designed for efficient and interactive chat-based applications. Despite its smaller size, it offers fast performance and reliable natural language understanding, making it ideal for real-time AI interactions on resource-constrained systems.
Run time: 1 second
1472 runs
0

Qwen/Qwen2.5-Coder-32B-Instruct

Qwen2.5-Coder-32B-Instruct is a powerful code-focused large language model with 32 billion parameters, fine-tuned for coding and instruction-based tasks. It excels in code generation, code completion, and understanding complex programming instructions across multiple languages.
Run time: 1 second
2533 runs
0

Qwen/Qwen2.5-7B-Instruct

Qwen 2.5 is the large language model of Qwen, offering advanced natural language understanding and generation capabilities. It’s designed to handle complex tasks with high accuracy, making it ideal for diverse AI applications.
Run time: 1 second
2609 runs
0

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