calme-2.4-qwen2-7b
| Property | Value |
|---|---|
| Base Model | Qwen2-7B |
| Developer | MaziyarPanahi |
| Model Size | 7 Billion parameters |
| Format Support | GGUF Quantization Available |
What is calme-2.4-qwen2-7b?
calme-2.4-qwen2-7b is a sophisticated fine-tuned version of the Qwen2-7B language model, specifically engineered to enhance performance across multiple benchmarks. This model represents a significant advancement in natural language processing capabilities, implementing the ChatML prompt template for improved interaction.
Implementation Details
The model utilizes a structured ChatML prompt format and offers both standard and GGUF quantized versions. Implementation is straightforward through the Transformers library, supporting both pipeline and direct model loading approaches.
- Supports high-level pipeline implementation
- Enables direct model loading via AutoTokenizer and AutoModelForCausalLM
- Includes GGUF quantized versions for efficient deployment
- Uses ChatML template for consistent input formatting
Core Capabilities
- Strong performance on IFEval (33.00 score on 0-shot)
- Impressive BBH performance (31.82 on 3-shot)
- Solid MMLU-PRO results (33.08 on 5-shot)
- Mathematical reasoning capabilities (18.35 on MATH Lvl 5)
- Overall average benchmark score of 22.52
Frequently Asked Questions
Q: What makes this model unique?
The model stands out for its balanced performance across various benchmarks and its implementation of the ChatML prompt template, making it particularly suitable for chat-based applications while maintaining strong analytical capabilities.
Q: What are the recommended use cases?
Based on its benchmark performance, the model is well-suited for tasks requiring logical reasoning, mathematical problem-solving, and general knowledge application. It's particularly effective in scenarios requiring few-shot learning and zero-shot inference.
