Instructions to use Gerwin/bert-for-pac with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Gerwin/bert-for-pac with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Gerwin/bert-for-pac")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Gerwin/bert-for-pac") model = AutoModelForSequenceClassification.from_pretrained("Gerwin/bert-for-pac", device_map="auto") - Notebooks
- Google Colab
- Kaggle
| language: | |
| - nl | |
| tags: | |
| - bert | |
| - passive | |
| - active | |
| license: apache-2.0 | |
| ## Dutch Fine-Tuned BERT For Passive/Active Voice Classification. | |
| ### Lijdende en Bedrijvende vorm classificatie voor zinnen | |
| #### Examples | |
| Try the following examples in the Hosted inference API: | |
| 1. Jan werd opgehaald door zijn moeder. | |
| 2. Wie niet weg is, is gezien | |
| 3. Ik ben van plan om morgen te gaan werken | |
| 4. De makelaar heeft het nieuwe huis verkocht aan de bewoners die iets verderop wonen. | |
| 5. De koekjes die mama had gemaakt waren door de jongens allemaal opgegeten. | |
| LABEL_0 = Active / Bedrijvend. LABEL_1 = Passive / Lijdend | |
| Answers (what they should be): | |
| 1. 1 | |
| 2. 1 | |
| 3. 0 | |
| 4. 0 | |
| 5. 1 | |
| #### Basic Information | |
| This model is fine-tuned on [BERTje](https://huggingface.co/GroNLP/bert-base-dutch-cased) for recognizing passive and active voice in Dutch sentences. | |
| Contact me at gerwindekruijf@gmail.com for further questions. | |
| Gerwin |