Instructions to use Xenova/LaMini-T5-61M with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers.js
How to use Xenova/LaMini-T5-61M with Transformers.js:
// ⚠️ Unknown pipeline tag
|
Download README.md from Xenova/LaMini-T5-61M: direct link, hf CLI and curl.
- Browser
- Download file 1.09 kB
-
https://huggingface.co/Xenova/LaMini-T5-61M/resolve/main/README.md
- Command line
-
hf download hf://Xenova/LaMini-T5-61M/README.md
-
curl -L -o README.md https://huggingface.co/Xenova/LaMini-T5-61M/resolve/main/README.md
1.09 kB
metadata
base_model: MBZUAI/LaMini-T5-61M
library_name: transformers.js
https://huggingface.co/MBZUAI/LaMini-T5-61M with ONNX weights to be compatible with Transformers.js.
Usage (Transformers.js)
If you haven't already, you can install the Transformers.js JavaScript library from NPM using:
npm i @huggingface/transformers
Example: Text-to-text generation.
import { pipeline } from '@huggingface/transformers';
const generator = await pipeline('text2text-generation', 'Xenova/LaMini-T5-61M');
const output = await generator('how can I become more healthy?', {
max_new_tokens: 100,
});
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).