Instructions to use danghaidang-passau/OwsEng with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use danghaidang-passau/OwsEng with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="danghaidang-passau/OwsEng")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("danghaidang-passau/OwsEng") model = AutoModelForMaskedLM.from_pretrained("danghaidang-passau/OwsEng") - Notebooks
- Google Colab
- Kaggle
Update model card with paper, repository links and metadata
#1
by nielsr HF Staff - opened
Hi there, I'm Niels from the Hugging Face community science team. I noticed this model card was still using the default template.
I've updated the model card to include:
- Metadata for the
text-classificationtask, the four languages supported (en, de, es, vi), and relevant tags likehate-speech. - Links to the associated research paper and the official GitHub repository.
- A summary of the model's background based on the paper abstract (continued pre-training on OWS data).
- The BibTeX citation for researchers using this model.
This information helps users understand the context of the work and makes the model more discoverable.