---
base_model: Salesforce/codegen-350M-mono
library_name: transformers.js
---

https://huggingface.co/Salesforce/codegen-350M-mono with ONNX weights to be compatible with Transformers.js.


## Usage (Transformers.js)

If you haven't already, you can install the [Transformers.js](https://huggingface.co/docs/transformers.js) JavaScript library from [NPM](https://www.npmjs.com/package/@huggingface/transformers) using:
```bash
npm i @huggingface/transformers
```

**Example:** Code completion w/ `Xenova/codegen-350M-mono`.
```js
import { pipeline } from "@huggingface/transformers";

// Create a text generation pipeline
const generator = await pipeline("text-generation", "Xenova/codegen-350M-mono");

// Define the prompt
const text = `def fib(n):
    """Calculates the nth Fibonacci number"""`;

// Generate a response
const output = await generator(text, { max_new_tokens: 45 });
console.log(output[0].generated_text);
```

---

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](https://huggingface.co/docs/optimum/index) and structuring your repo like this one (with ONNX weights located in a subfolder named `onnx`).