code2022/SmolLM2-135M-Instruct-Paraphrase

license: apache-2.0 datasets:

• google-research-datasets/paws language:
• en metrics:
• accuracy base_model:
• HuggingFaceTB/SmolLM2-135M-Instruct pipeline_tag: text-generation

Introduction

This repository is part of playbook for experiments on fine tuning small language models using LoRA, exporting them to ONNX and running them locally using ONNX compatibale runtime like javascript(node js) and WASM (browser)

Before you start

• Clone the repository https://github.com/code2k13/onnx_javascript_browser_inference
• Copy all files from this repository to the model_files directory of the cloned github repository.
• Run npm install

To run NodeJS example (NodeJS + onnx-runtime, server side)

• Simple run node app.js This is what you should see

To run web browser based demo (WASM based in-browser inference)

• Simply access web.html from a local server (example http://localhost:3000/web.html)

This is what you should see

Citation

@misc{allal2024SmolLM,
      title={SmolLM - blazingly fast and remarkably powerful}, 
      author={Loubna Ben Allal and Anton Lozhkov and Elie Bakouch and Leandro von Werra and Thomas Wolf},
      year={2024},
}