Qwen1.5-14B
| Property | Value |
|---|---|
| Parameter Count | 14.2B |
| License | tongyi-qianwen |
| Tensor Type | BF16 |
| Paper | arXiv:2309.16609 |
| Context Length | 32K tokens |
What is Qwen1.5-14B?
Qwen1.5-14B 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 provide robust language understanding and generation capabilities.
Implementation Details
The model architecture incorporates several sophisticated components including SwiGLU activation, attention QKV bias, and group query attention. It features a hybrid attention mechanism combining sliding window attention with full attention capabilities. The implementation requires transformers>=4.37.0 and has been optimized for efficient processing.
- Advanced transformer architecture with SwiGLU activation
- Improved tokenizer for multiple natural languages and code
- 32K context length support
- No requirement for trust_remote_code
Core Capabilities
- Multilingual support for both base and chat models
- Enhanced performance in chat model variants
- Stable long-context processing
- Versatile application in post-training scenarios
Frequently Asked Questions
Q: What makes this model unique?
Qwen1.5-14B stands out for its comprehensive improvements over previous versions, including stable 32K context length support, enhanced multilingual capabilities, and significant performance improvements in chat models, all while maintaining a streamlined implementation that doesn't require trust_remote_code.
Q: What are the recommended use cases?
The model is primarily designed for post-training applications such as Supervised Fine-Tuning (SFT), RLHF, and continued pretraining. It's not recommended to use the base model directly for text generation without additional training.
