Qwen1.5-32B
| Property | Value |
|---|---|
| Parameter Count | 32.5B |
| Tensor Type | BF16 |
| License | tongyi-qianwen-research |
| Paper | View Paper |
| Context Length | 32K tokens |
What is Qwen1.5-32B?
Qwen1.5-32B is a beta version of Qwen2, representing a significant advancement in transformer-based language models. It's part of a comprehensive series that includes models ranging from 0.5B to 72B parameters. This particular 32B parameter variant combines sophisticated architecture with extensive pretraining to deliver robust language processing capabilities.
Implementation Details
The model is built on an advanced Transformer architecture featuring several key technical innovations:
- SwiGLU activation function for enhanced performance
- Attention QKV bias implementation
- Group Query Attention (GQA) specifically for the 32B version
- Improved tokenizer optimized for multiple languages and code
- Requires transformers>=4.37.0 for proper functionality
Core Capabilities
- Stable 32K context length support
- Multilingual processing for both base and chat variants
- Advanced text generation capabilities
- Suitable for post-training applications (SFT, RLHF, continued pretraining)
Frequently Asked Questions
Q: What makes this model unique?
This model stands out for its combination of large-scale parameters (32.5B), extensive context length support (32K), and advanced architectural features like GQA and SwiGLU activation. It's part of the Qwen1.5 series, which represents a significant improvement over previous versions in terms of performance and capabilities.
Q: What are the recommended use cases?
While the base model isn't recommended for direct text generation, it's ideal for research applications and can be fine-tuned through various post-training methods like SFT, RLHF, or continued pretraining for specific use cases. It's particularly suitable for developers and researchers looking to build specialized language models.
