| | --- |
| | library_name: transformers.js |
| | base_model: oxyapi/oxy-1-micro |
| | --- |
| | |
| | https://huggingface.co/oxyapi/oxy-1-micro 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 |
| | ``` |
| |
|
| | You can then use the model to generate text like this: |
| |
|
| | ```js |
| | import { pipeline } from "@huggingface/transformers"; |
| | |
| | // Create a text generation pipeline |
| | const generator = await pipeline( |
| | "text-generation", |
| | "onnx-community/oxy-1-micro", |
| | { dtype: "q4" }, |
| | ); |
| | |
| | // Define the list of messages |
| | const messages = [ |
| | { role: "system", content: "You are a wise old wizard in a mystical land. A traveler approaches you seeking advice." }, |
| | { role: "user", content: "Where is the nearest inn?" }, |
| | ]; |
| | |
| | // Generate a response |
| | const output = await generator(messages, { max_new_tokens: 256, do_sample: false }); |
| | console.log(output[0].generated_text.at(-1).content); |
| | ``` |
| |
|
| | <details> |
| |
|
| | <summary>See example output</summary> |
| |
|
| | ``` |
| | Greetings, traveler! I am here to guide you through this enchanted realm. The nearest inn is located not far from my humble abode. It is called "The Quiet Haven," and it is nestled on a quiet path just beyond my property. You can find it by following the winding paths of the forest. May I assist you further? |
| | ``` |
| | </details> |
| |
|
| | --- |
| |
|
| | 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`). |