| base_model: facebook/nougat-small | |
| library_name: transformers.js | |
| pipeline_tag: image-to-text | |
| tags: | |
| - vision | |
| - nougat | |
| https://huggingface.co/facebook/nougat-small 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/@xenova/transformers) using: | |
| ```bash | |
| npm i @xenova/transformers | |
| ``` | |
| You can then use the model to convert images of scientific PDFs into markdown like this: | |
| ```js | |
| import { pipeline } from '@xenova/transformers'; | |
| // Create an image-to-text pipeline | |
| const pipe = await pipeline('image-to-text', 'Xenova/nougat-small'); | |
| // Generate markdown | |
| const url = 'https://huggingface.co/datasets/Xenova/transformers.js-docs/resolve/main/nougat_paper.png'; | |
| const output = await pipe(url, { | |
| min_length: 1, | |
| max_new_tokens: 40, | |
| bad_words_ids: [[pipe.tokenizer.unk_token_id]], | |
| }); | |
| console.log(output); | |
| // [{ generated_text: "# Nougat: Neural Optical Understanding for Academic Documents\n\nLukas Blecher\n\nCorrespondence to: lblecher@meta.com\n\nGuillem Cucur" }] | |
| ``` | |
| --- | |
| 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`). |