onnx-community/Jan-nano-ONNX
By onnx-community · ↓ 11 · ♥ 2 · Updated 2025-06-26
What's in this repo
This page lists the files in onnx-community/Jan-nano-ONNX, including model_fp16.onnx, model_q4f16.onnx.
- 2 ONNX models (.onnx files)
- 18 files, including 6 .json, 2 .onnx, 2 .onnx_data, 2 .onnx_data_1, 1 .md, 1 .jinja
- Last updated 2025-06-26
ONNX files
How to use
These ONNX files can be loaded with ONNX Runtime. To inspect a model graph, upload the file to the Netron viewer. Download links point to the original files on Hugging Face.
README
https://huggingface.co/Menlo/Jan-nano with ONNX weights to be compatible with Transformers.js.
Jan-Nano: An Agentic Model

Authors: Alan Dao, Bach Vu Dinh, Thinh Le
Overview
Jan-Nano is a compact 4-billion parameter language model specifically designed and trained for deep research tasks. This model has been optimized to work seamlessly with Model Context Protocol (MCP) servers, enabling efficient integration with various research tools and data sources.
Usage (Transformers.js)
If you haven't already, you can install the Transformers.js JavaScript library from NPM using:
npm i @huggingface/transformers
Example: Text-generation with onnx-community/Jan-nano-ONNX.
import { pipeline, TextStreamer } from "@huggingface/transformers";
// Create a text generation pipeline
const generator = await pipeline(
"text-generation",
"onnx-community/Jan-nano-ONNX",
{ dtype: "q4f16" },
);
// Define the list of messages
const messages = [
{ role: "system", content: "You are a helpful assistant." },
{ role: "user", content: "Tell me a joke." },
];
// Generate a response
const output = await generator(messages, {
max_new_tokens: 512,
do_sample: false,
streamer: new TextStreamer(generator.tokenizer, { skip_prompt: true, skip_special_tokens: true}),
});
console.log(output[0].generated_text.at(-1).content);
Note: Having a separate repo for ONNX weights is intended to be a temporary solution until WebML gains more traction. If you would like to make your models web-ready, we recommend converting to ONNX using 🤗 Optimum and structuring your repo like this one (with ONNX weights located in a subfolder named onnx).
Model info
Created: 2025-06-17
Updated: 2025-06-26
View on Hugging Face