Instructions to use Shaer-AI/ARBERT-base-submeter-classifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Shaer-AI/ARBERT-base-submeter-classifier with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Shaer-AI/ARBERT-base-submeter-classifier")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Shaer-AI/ARBERT-base-submeter-classifier") model = AutoModelForSequenceClassification.from_pretrained("Shaer-AI/ARBERT-base-submeter-classifier", device_map="auto") - Notebooks
- Google Colab
- Kaggle
| class_id,checkpoint_label,semantic_label | |
| 0,LABEL_0,baseet complete | |
| 1,LABEL_1,baseet mukhala | |
| 2,LABEL_2,hazaj majzuu | |
| 3,LABEL_3,kamel ahuth | |
| 4,LABEL_4,kamel complete | |
| 5,LABEL_5,kamel majzuu | |
| 6,LABEL_6,khafif complete | |
| 7,LABEL_7,khafif majzuu | |
| 8,LABEL_8,madeed majzuu | |
| 9,LABEL_9,mudari majzuu | |
| 10,LABEL_10,mujtath majzuu | |
| 11,LABEL_11,munsarih complete | |
| 12,LABEL_12,muqtadab majzuu | |
| 13,LABEL_13,mutadarak complete | |
| 14,LABEL_14,mutadarak mashture | |
| 15,LABEL_15,mutaqarib complete | |
| 16,LABEL_16,rajaz complete | |
| 17,LABEL_17,rajaz majzuu | |
| 18,LABEL_18,rajaz mashture | |
| 19,LABEL_19,ramel complete | |
| 20,LABEL_20,ramel majzuu | |
| 21,LABEL_21,saree complete | |
| 22,LABEL_22,taweel complete | |
| 23,LABEL_23,wafer complete | |
| 24,LABEL_24,wafer majzuu | |