onnx-community/EXAONE-3.5-2.4B-Instruct

https://huggingface.co./LGAI-EXAONE/EXAONE-3.5-2.4B-Instruct with ONNX weights to be compatible with Transformers.js.

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 w/ EXAONE-3.5-2.4B-Instruct:

import { pipeline } from "@huggingface/transformers";

// Create a text generation pipeline
const generator = await pipeline(
  "text-generation",
  "onnx-community/EXAONE-3.5-2.4B-Instruct",
  { 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: 128 });
console.log(output[0].generated_text.at(-1).content);

See example output

Sure! Here's a light joke for you:

Why don't scientists trust atoms?

Because they make up everything! 

I hope you found that amusing! If you want another one, feel free to ask!

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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).