Serpens Opus 14B Exp
Serpens-Opus-14B-Exp is a 14-billion-parameter model based on the Qwen 2.5 14B architecture, designed to enhance reasoning capabilities for general-purpose reasoning and Q&A tasks.
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Release Time : 2/25/2025
Model Overview
This model is optimized for general reasoning and Q&A tasks, excelling in contextual understanding, logical reasoning, and multi-step problem-solving. Through fine-tuning with long-chain reasoning models and specialized datasets, it improves comprehension, structured responses, and conversational intelligence.
Model Features
Enhanced general knowledge
Covers multi-domain knowledge, improving answer accuracy and the ability to generate coherent responses.
Improved instruction following
Significantly enhances understanding and execution of complex instructions, generates structured responses, and maintains consistency in long conversations.
Diverse adaptability
More resilient to various prompts, capable of flexibly handling open-ended and structured questions.
Long-context support
Supports input contexts of up to 128K tokens, with single outputs reaching 8K tokens, suitable for generating detailed responses.
Multilingual capabilities
Supports over 29 languages, including English, Chinese, French, Spanish, and more.
Model Capabilities
Text generation
Logical reasoning
Multilingual support
Long-text generation
Structured data processing
Use Cases
General reasoning
Logical reasoning
Suitable for logical reasoning, diverse Q&A, and common-sense problem-solving.
Educational assistance
Educational explanations
Provides explanations, summaries, and research-based answers for students, educators, and general users.
Conversational AI & chatbots
Intelligent dialogue systems
Ideal for building intelligent dialogue systems requiring contextual understanding and dynamic response generation.
Multilingual applications
Global communication
Supports global communication, translation, and multilingual content generation.
Structured data processing
Data science & automation
Can analyze and generate structured outputs like tables and JSON, suitable for data science and automation.
Long-text generation
Article generation
Capable of generating long-form content like articles and reports while maintaining overall coherence.
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