Qwen1.5-14B-Chat
| Property | Value |
|---|---|
| Parameter Count | 14.2B |
| License | Tongyi-Qianwen |
| Architecture | Transformer-based decoder-only |
| Context Length | 32K tokens |
| Paper | Research Paper |
What is Qwen1.5-14B-Chat?
Qwen1.5-14B-Chat is a beta version of Qwen2, representing a significant advancement in transformer-based language models. This 14.2B parameter model is part of a comprehensive series ranging from 0.5B to 72B parameters, designed to deliver enhanced chat capabilities and multilingual support.
Implementation Details
The model is built on an advanced transformer architecture incorporating several key technological improvements including SwiGLU activation, attention QKV bias, and group query attention. It utilizes BF16 tensor type and requires transformers>=4.37.0 for proper implementation.
- Stable 32K context length support
- Improved tokenizer for multiple natural languages and code
- Advanced training through supervised finetuning and direct preference optimization
- No requirement for trust_remote_code
Core Capabilities
- Enhanced chat performance with improved human preference metrics
- Robust multilingual support for both base and chat models
- Efficient text generation and processing
- Available in multiple quantized versions (GPTQ, AWQ, GGUF)
Frequently Asked Questions
Q: What makes this model unique?
The model stands out for its combination of large-scale parameters (14.2B), extensive context length (32K), and improved chat capabilities, all while maintaining strong multilingual support and requiring no trust_remote_code.
Q: What are the recommended use cases?
This model is particularly well-suited for chat applications, multilingual text generation, and conversational AI implementations where high performance and reliability are crucial. It's ideal for both research and production environments requiring advanced language understanding and generation capabilities.
