faster-reasoning

This repository includes a small example showing how to load the open-source Mistral-7B language model with the Hugging Face transformers library. The script mistral_layers.py loads the model, prints a summary of each transformer layer, and generates a short sample response.

Requirements

• Python 3.8+
• torch
• transformers

Install dependencies with:

pip install torch transformers

Usage

Run the script to view the model layers and a sample generation:

python3 mistral_layers.py

Loading the model requires downloading the weights from Hugging Face on the first run. Ensure you have internet access and enough disk space (~15GB).

Custom architecture implementation

The file mistral_full.py provides a minimal PyTorch implementation of the Mistral model. It mirrors the architecture used by the released 7B weights so you can experiment with changing individual layers. The helper load_pretrained function loads the official weights from Hugging Face into this custom model.

To print a short summary of each layer run:

python3 mistral_full.py

The example relies on the same torch and transformers dependencies listed above.