Uw U 7 B Instruct

Introduction

UWU-7B-INSTRUCT is a general-purpose reasoning model fine-tuned on the FineQwQ-142K dataset. Unlike previous models, it aims to provide a more versatile reasoning capability and demonstrates proficiency in tasks such as counting letters in words, exemplified by its ability to pass the "strawberry test."

Architecture

The UWU-7B-INSTRUCT model is based on the Qwen/Qwen2.5-7B architecture. This foundation enables the model to perform tasks related to text generation and conversational applications, leveraging the strengths of the underlying architecture for enhanced reasoning.

Training

The model is fully fine-tuned on the FineQwQ-142K dataset. This comprehensive fine-tuning process allows the model to perform a wide range of reasoning tasks, making it a versatile tool for general-purpose applications.

Guide: Running Locally

To run the UWU-7B-INSTRUCT model locally, follow these steps:

1. Clone the Repository:

   • Navigate to the model's GitHub repository and clone it to your local machine.

2. Install Dependencies:

   • Ensure you have Python and the necessary libraries installed, such as transformers and torch.

3. Load the Model:

   • Use the Hugging Face transformers library to load the model and tokenizer.

4. Run Inference:

   • Prepare your input data and use the model to generate text or perform reasoning tasks.

5. Cloud GPU Recommendation:

   • For optimal performance, particularly for large models, consider using cloud-based GPU services such as AWS EC2, Google Cloud Platform, or Azure.

License

The UWU-7B-INSTRUCT model is released under the Apache 2.0 license, allowing for both academic and commercial use with proper attribution.