Text Classification
Transformers
PyTorch
Arabic
bert
sentiment analysis
classification
arabic dialect
tunisian dialect
Instructions to use AhmedBou/TuniBert with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use AhmedBou/TuniBert with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="AhmedBou/TuniBert")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("AhmedBou/TuniBert") model = AutoModelForSequenceClassification.from_pretrained("AhmedBou/TuniBert") - Notebooks
- Google Colab
- Kaggle
| {"unk_token": "[UNK]", "sep_token": "[SEP]", "pad_token": "[PAD]", "cls_token": "[CLS]", "mask_token": "[MASK]", "special_tokens_map_file": null, "full_tokenizer_file": null, "tokenizer_file": null, "name_or_path": "asafaya/bert-base-arabic"} |