Instructions to use VARabic/Sentence-ALDi with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use VARabic/Sentence-ALDi with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="VARabic/Sentence-ALDi")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("VARabic/Sentence-ALDi") model = AutoModelForSequenceClassification.from_pretrained("VARabic/Sentence-ALDi", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Delete tokenizer.json
#4
by rabeya100X - opened
Removing stale tokenizer.json (32K vocab) as discussed in transformers PR #48973 so AutoTokenizer relies on vocab.txt (100K vocab) via tokenizer_config.json.
AMR-KELEG changed pull request status to merged