Instructions to use andrzej/SmolLM2-135M-ONNX with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers.js
How to use andrzej/SmolLM2-135M-ONNX with Transformers.js:
// npm i @huggingface/transformers import { pipeline } from '@huggingface/transformers'; // Allocate pipeline const pipe = await pipeline('text-generation', 'andrzej/SmolLM2-135M-ONNX');
SmolLM2-135M (ONNX, mirror)
Source: onnx-community/SmolLM2-135M-ONNX, an ONNX version of HuggingFaceTB/SmolLM2-135M by Hugging Face TB.
Conversion: none here. Every file is copied unchanged from onnx-community/SmolLM2-135M-ONNX at revision d0ae6834f1df45e0e95b5fdae95e536f9ca7cd3f, which was converted with the onnx-community conversion space. Only the files the app loads are included: the int8 build (onnx/model_int8.onnx) and the fp32 build (onnx/model.onnx with its external data onnx/model.onnx_data), plus config and tokenizer files. SHA-256 values were checked against the source repository.
This repository exists for in-browser demos with Transformers.js 4.3.2 (an educational app that compares base, SFT and SFT + DPO versions of SmolLM2-135M side by side). Language: English. The model can produce inaccurate or made-up text.
Licence: Apache 2.0, as HuggingFaceTB/SmolLM2-135M. All credit for the model goes to its authors.
| File | Bytes | SHA-256 |
|---|---|---|
config.json |
1,035 | 2c5f23fddabecdf9c47d0048f555899822ec87ec4a28169393840ac7e74192c4 |
generation_config.json |
116 | 8e3a8ff6f89c519e9c88f8da84425fb9cc88f99d45f99ead478fff9b3692f48d |
tokenizer.json |
2,053,526 | 139d2f4b4919b90953bdd3c0c40c94c9b23074799a766508dc3bf5eb8ab73351 |
tokenizer_config.json |
3,687 | b5d746195c39b6aa173e7f70baf01eae62d26873a27d48ae0b62b4d99d4b9fbd |
onnx/model_int8.onnx |
135,658,354 | 50ba80511ce74634d232a043b6c37775cca756b826b49d0a4a8eff958c4bbcc9 |
onnx/model.onnx |
199,002 | de4f7dbed6420825147b1fd97d7ea000042ad667ce30316bedd87a3ed49c48b1 |
onnx/model.onnx_data |
540,157,184 | 3ffe0420181424138de643144c94bd4c30126221cc636590f3ccb2fa352ae602 |
Citation (upstream)
@misc{allal2025smollm2smolgoesbig,
title={SmolLM2: When Smol Goes Big -- Data-Centric Training of a Small Language Model},
author={Loubna Ben Allal and Anton Lozhkov and Elie Bakouch and Gabriel Martín Blázquez and Guilherme Penedo and Lewis Tunstall and Andrés Marafioti and Hynek Kydlíček and Agustín Piqueres Lajarín and Vaibhav Srivastav and Joshua Lochner and Caleb Fahlgren and Xuan-Son Nguyen and Clémentine Fourrier and Ben Burtenshaw and Hugo Larcher and Haojun Zhao and Cyril Zakka and Mathieu Morlon and Colin Raffel and Leandro von Werra and Thomas Wolf},
year={2025},
eprint={2502.02737},
archivePrefix={arXiv},
primaryClass={cs.CL},
url={https://arxiv.org/abs/2502.02737},
}
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