Instructions to use Xenova/vit-gpt2-image-captioning with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers.js
How to use Xenova/vit-gpt2-image-captioning with Transformers.js:
// npm i @huggingface/transformers import { pipeline } from '@huggingface/transformers'; // Allocate pipeline const pipe = await pipeline('image-to-text', 'Xenova/vit-gpt2-image-captioning');
metadata
base_model: nlpconnect/vit-gpt2-image-captioning
library_name: transformers.js
pipeline_tag: image-to-text
tags:
- image-captioning
https://huggingface.co/nlpconnect/vit-gpt2-image-captioning 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 and structuring your repo like this one (with ONNX weights located in a subfolder named onnx).