The Phi-3-Medium-4K-Instruct is a 14B parameters, lightweight, open model trained with the Phi-3 datasets that includes both synthetic data and the filtered publicly available websites data with a focus on high-quality and reasoning dense properties.
Description:
The Phi-3-Medium-4K-Instruct is a 14B parameters, lightweight, state-of-the-art open model trained with the Phi-3 datasets that includes both synthetic data and the filtered publicly available websites data with a focus on high-quality and reasoning dense properties. The model supports 4K context length (in tokens).
The model has underwent a post-training process that incorporates both supervised fine-tuning and direct preference optimization for the instruction following and safety measures. When assessed against benchmarks testing common sense, language understanding, math, code, long context and logical reasoning, Phi-3-Medium-4K-Instruct showcased a robust and state-of-the-art performance among models with less than 13 billion parameters.
The model is licensed under the MIT license
Terms of use:
By accessing this model, you are agreeing to the Terms and Conditions of the MIT License.
References(s):
- Phi-3-medium-4k-instruct Model Card
- Phi-3 blogpost
Model Architecture:
Architecture Type: Transformer
Input:
Input Format: Text
Input Parameters: None
Output:
Output Format: Text
Output Parameters: None
Software Integration:
Supported Hardware Platform(s): RTX 4090, Ada GPUs
Supported Operating System(s): Windows
Inference:
TRT-LLM Inference Engine
Windows Setup with TRT-LLM
Test Hardware:
RTX 4090