https://huggingface.co/gpt2 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 @xenova/transformers
You can then use the model to generate text as follows:
import { pipeline } from '@xenova/transformers';
// Create a text-generation pipeline
const generator = await pipeline('text-generation', 'Xenova/gpt2');
// Generate text (default parameters)
const text = 'Once upon a time,';
const output = await generator(text);
console.log(output);
// [{ generated_text: 'Once upon a time, I was in a room with a woman who was very attractive. She was' }]
// Generate text (custom parameters)
const output2 = await generator(text, {
max_new_tokens: 20,
do_sample: true,
top_k: 5,
});
console.log(output2);
// [{ generated_text: 'generated_text: 'Once upon a time, the first thing I did was put a small piece of paper on a table. I put the paper' }]
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
).
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Inference API (serverless) does not yet support transformers.js models for this pipeline type.