Qwen2.5-1.5B-apeach
| Property | Value |
|---|---|
| Parameter Count | 1.54B |
| Tensor Type | F32 |
| Downloads | 16,738 |
| Author | jason9693 |
What is Qwen2.5-1.5B-apeach?
Qwen2.5-1.5B-apeach is a powerful transformer-based language model built on the Qwen2 architecture, specifically designed for text classification and generation tasks. With 1.54 billion parameters, this model represents a balanced approach between computational efficiency and performance capabilities.
Implementation Details
The model is implemented using the Hugging Face Transformers library and supports F32 tensor operations. It's optimized for text-generation-inference (TGI) endpoints, making it suitable for production deployments.
- Built on Qwen2 architecture
- Supports Safetensors format
- Optimized for inference endpoints
- Full F32 precision support
Core Capabilities
- Text Classification
- Text Generation
- Transformer-based processing
- Production-ready inference
Frequently Asked Questions
Q: What makes this model unique?
This model stands out for its implementation of the Qwen2 architecture at a moderate scale of 1.54B parameters, making it practical for both research and production use cases while maintaining good performance characteristics.
Q: What are the recommended use cases?
The model is particularly well-suited for text classification tasks and general text generation applications, especially in scenarios where deployment through text-generation-inference endpoints is desired.
