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!

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).

Downloads last month
10
Inference Providers NEW
This model is not currently available via any of the supported Inference Providers.
The model cannot be deployed to the HF Inference API: The HF Inference API does not support model that require custom code execution.

Model tree for onnx-community/EXAONE-3.5-2.4B-Instruct

Quantized
(8)
this model