Instructions to use rolf-mozilla/tinybert-address-autofill with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers.js
How to use rolf-mozilla/tinybert-address-autofill with Transformers.js:
// npm i @huggingface/transformers import { pipeline } from '@huggingface/transformers'; // Allocate pipeline const pipe = await pipeline('text-classification', 'rolf-mozilla/tinybert-address-autofill');
|
Download README.md from rolf-mozilla/tinybert-address-autofill: direct link, hf CLI and curl.
- Browser
- Download file 599 Bytes
-
https://huggingface.co/rolf-mozilla/tinybert-address-autofill/resolve/main/README.md
- Command line
-
hf download hf://rolf-mozilla/tinybert-address-autofill/README.md
-
curl -L -o README.md https://huggingface.co/rolf-mozilla/tinybert-address-autofill/resolve/main/README.md
599 Bytes
| license: mpl-2.0 | |
| base_model: huawei-noah/TinyBERT_General_4L_312D | |
| tags: [autofill, form-field-classification, onnx, transformers.js] | |
| # tinybert-address-autofill (v0.2.2) | |
| Firefox address-autofill field classifier, retrained from the jt4qd v2 baseline | |
| **without the `**` input-type marker** (`strip_type_marker=True`) so training | |
| matches Firefox inference. jt4qd params (bb, encoder_layers=0, pooling=cls, | |
| lr=3e-5, batch=64, epochs=25). **Training data:** current/refreshed | |
| train/val/test. **Offline (no-`**`):** total 0.8897 / close 0.9133. | |
| Only `onnx/model_quantized.onnx` (q8) is shipped. | |