bennett-tan/phi-4-mini-instruct-merged
The bennett-tan/phi-4-mini-instruct-merged is a 3.8 billion parameter instruction-tuned causal language model developed by bennett-tan. This model is a finetuned variant of the phi3 architecture, optimized for faster training using Unsloth and Huggingface's TRL library. It is designed for general instruction-following tasks, leveraging its efficient training methodology.
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Model Overview
The bennett-tan/phi-4-mini-instruct-merged is a 3.8 billion parameter instruction-tuned language model. It is a finetuned version of the phi3 architecture, developed by bennett-tan.
Key Characteristics
- Architecture: Based on the phi3 model family.
- Parameter Count: 3.8 billion parameters.
- Training Efficiency: This model was finetuned using Unsloth and Huggingface's TRL library, enabling a 2x faster training process compared to standard methods.
- Context Length: Supports a context length of 131,072 tokens.
Use Cases
This model is suitable for various instruction-following applications where a compact yet capable language model is required. Its efficient training process suggests it could be a good candidate for scenarios prioritizing faster iteration and deployment.