File size: 1,612 Bytes
2467259 8eecec7 f2b39f8 8eecec7 2467259 d282cf5 8eecec7 f2b39f8 8eecec7 f2b39f8 8eecec7 4f5b807 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 | ---
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](https://ashishware.com/2025/11/16/slm_in_browser/) 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},
}
``` |