| | --- |
| | license: apache-2.0 |
| | base_model: |
| | - HuggingFaceTB/SmolLM2-360M-Instruct |
| | pipeline_tag: text-generation |
| | tags: |
| | - 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 |
| | ``` |
| |
|
| | You can then generate text as follows: |
| | ```js |
| | import { pipeline } from '@huggingface/transformers'; |
| | |
| | // Create a text generation pipeline |
| | const generator = await pipeline('text-generation', 'eduardoworrel/SmolLM2-360M-Instruct', { |
| | device: 'webgpu', // <- Run on WebGPU |
| | }); |
| | |
| | // Define the list of messages |
| | const messages = [ |
| | { role: "system", content: "You are a helpful assistant." }, |
| | { role: "user", content: "What is the capital of Brazil?" }, |
| | ]; |
| | |
| | // Generate a response |
| | const output = await generator(messages, { max_new_tokens: 128 }); |
| | console.log(output[0].generated_text.at(-1).content); |
| | ``` |