cs-552-2026-aaty/math_model
The cs-552-2026-aaty/math_model is a fine-tuned version of the Qwen3-1.7B architecture, developed by cs-552-2026-aaty. This model has been trained using Supervised Fine-Tuning (SFT) with the TRL framework. While specific parameter count and context length are not detailed, its foundation on Qwen3-1.7B suggests a compact yet capable model. It is designed for general text generation tasks, as indicated by its quick start example.
Loading preview...
Model Overview
The cs-552-2026-aaty/math_model is a language model developed by cs-552-2026-aaty, based on the Qwen/Qwen3-1.7B architecture. This model has undergone Supervised Fine-Tuning (SFT) using the TRL library, a framework for Transformer Reinforcement Learning.
Key Characteristics
- Base Model: Fine-tuned from Qwen/Qwen3-1.7B.
- Training Method: Utilizes Supervised Fine-Tuning (SFT).
- Frameworks: Trained with TRL (version 1.3.0), Transformers (version 5.7.0), Pytorch (version 2.10.0+cu128), Datasets (version 4.8.5), and Tokenizers (version 0.22.2).
Potential Use Cases
This model is suitable for various text generation tasks, leveraging its fine-tuned capabilities derived from the Qwen3-1.7B base. While specific mathematical optimization is not detailed in the README, its name suggests a potential focus or aptitude for math-related queries or reasoning, which would require further evaluation. The provided quick start example demonstrates its use for open-ended question answering and text completion.