MaziyarPanahi/calme-2.1-phi3-4b
MaziyarPanahi/calme-2.1-phi3-4b is a 4 billion parameter language model fine-tuned by MaziyarPanahi using DPO on Microsoft's Phi-3-mini-4k-instruct architecture. This model is designed for instruction-following tasks, leveraging its base model's capabilities. It utilizes a 4096-token context length and is suitable for general conversational AI applications requiring a compact yet capable model.
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Model Overview
MaziyarPanahi/calme-2.1-phi3-4b is a 4 billion parameter language model developed by MaziyarPanahi. It is a fine-tuned version of microsoft/Phi-3-mini-4k-instruct, utilizing Direct Preference Optimization (DPO) for enhanced performance. This model is built upon the Phi-3 architecture, known for its efficiency and capability in smaller parameter counts.
Key Capabilities and Performance
This model is designed for instruction-following and general conversational tasks. Its performance has been evaluated on the Open LLM Leaderboard, showing a balanced average score across various benchmarks. Notable scores include:
- IFEval (0-Shot): 55.25
- BBH (3-Shot): 38.12
- MMLU (5-Shot): 68.96
- GSM8k (5-Shot): 72.25
These metrics indicate its proficiency in reasoning, common sense, and mathematical problem-solving relative to its size.
Prompt Template
The model uses the ChatML prompt format, which is standard for many instruction-tuned models, facilitating clear role separation between system, user, and assistant messages.
Use Cases
This model is suitable for applications requiring a compact yet effective language model for tasks such as:
- General-purpose chatbots
- Instruction-following agents
- Text generation where efficiency and moderate performance are key