Instructions to use Xenova/tiny-random-ErnieForSequenceClassification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers.js
How to use Xenova/tiny-random-ErnieForSequenceClassification with Transformers.js:
// npm i @huggingface/transformers import { pipeline } from '@huggingface/transformers'; // Allocate pipeline const pipe = await pipeline('text-classification', 'Xenova/tiny-random-ErnieForSequenceClassification');
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base_model: hf-internal-testing/tiny-random-ErnieForSequenceClassification
library_name: transformers.js
---
https://huggingface.co/hf-internal-testing/tiny-random-ErnieForSequenceClassification with ONNX weights to be compatible with Transformers.js.
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`). |