DeepSeek-Coder-V2-Instruct-FP8
| Property | Value |
|---|---|
| Parameter Count | 236B |
| Model Type | Instruction-tuned Code Generation |
| License | deepseek-license |
| Quantization | FP8 (8-bit) |
| Architecture | DeepSeek-Coder-V2-Instruct |
What is DeepSeek-Coder-V2-Instruct-FP8?
DeepSeek-Coder-V2-Instruct-FP8 is an optimized version of the original DeepSeek-Coder-V2-Instruct model, specifically designed for efficient deployment while maintaining high performance. Through FP8 quantization of weights and activations, it achieves approximately 50% reduction in disk size and GPU memory requirements, enabling deployment on just 4 H100 GPUs instead of 8.
Implementation Details
The model employs symmetric per-tensor quantization for linear operators within transformer blocks, utilizing AutoFP8 with 512 sequences of UltraChat for calibration. It's compatible with vLLM >= 0.5.2 and maintains impressive performance metrics, achieving an 88.98 average score on the HumanEval+ benchmark.
- FP8 quantization for weights and activations
- 50% reduction in memory footprint
- Compatible with vLLM deployment
- Optimized for 4xH100 GPU setup
Core Capabilities
- High-performance code generation
- Assistant-like chat functionality
- English language support
- Commercial and research applications
- Improved benchmark performance compared to base model
Frequently Asked Questions
Q: What makes this model unique?
The model's distinctive feature is its efficient FP8 quantization that reduces resource requirements while maintaining or even improving performance metrics compared to the original model, as evidenced by its HumanEval+ benchmark scores.
Q: What are the recommended use cases?
The model is specifically designed for commercial and research applications in English, particularly for code generation and assistant-like chat interactions. It's optimized for deployment in resource-conscious environments while maintaining high performance standards.
