Text Classification
Transformers
Safetensors
Arabic
deberta-v2
Generated from Trainer
subjectivity-detection
news
arabic
Instructions to use AIWizards/mdeberta-v3-base-subjectivity-arabic with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use AIWizards/mdeberta-v3-base-subjectivity-arabic with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="AIWizards/mdeberta-v3-base-subjectivity-arabic")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("AIWizards/mdeberta-v3-base-subjectivity-arabic") model = AutoModelForSequenceClassification.from_pretrained("AIWizards/mdeberta-v3-base-subjectivity-arabic", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Improve model card: Add text-classification pipeline tag, update license, expand sections, and add usage/code
#1
by nielsr HF Staff - opened
This PR improves the model card for mdeberta-v3-base-subjectivity-arabic by:
- Adding the
pipeline_tag: text-classificationfor better discoverability. - Updating the license from
mittocc-by-4.0, as specified in the original GitHub repository. - Adding relevant
subjectivity-detection,news, andarabictags for improved searchability. - Populating the "Model description", "Intended uses & limitations", and "Training and evaluation data" sections with details from the paper abstract and GitHub README.
- Adding a "How to use" section with a Python code example for inference.
- Including a "Code" section with a direct link to the GitHub repository.
- Adding a "Citation" section with the BibTeX entry from the project's GitHub README.
MatteoFasulo changed pull request status to merged