Text Classification
Transformers
Safetensors
Arabic
quality_classifier
feature-extraction
quality-classifier
data-filtering
pretraining
custom_code
Instructions to use AdaMLLab/mmBERT-Arabic-Quality-Classifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use AdaMLLab/mmBERT-Arabic-Quality-Classifier with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="AdaMLLab/mmBERT-Arabic-Quality-Classifier", trust_remote_code=True)# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("AdaMLLab/mmBERT-Arabic-Quality-Classifier", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
| { | |
| "architectures": [ | |
| "QualityClassifierModel" | |
| ], | |
| "auto_map": { | |
| "AutoConfig": "merged_model.QualityClassifierConfig", | |
| "AutoModel": "merged_model.QualityClassifierModel" | |
| }, | |
| "base_model_name": "jhu-clsp/mmBERT-small", | |
| "dropout": 0.2, | |
| "dtype": "float32", | |
| "hidden_dim": 256, | |
| "id2label": { | |
| "0": "LABEL_0" | |
| }, | |
| "label2id": { | |
| "LABEL_0": 0 | |
| }, | |
| "model_type": "quality_classifier", | |
| "transformers_version": "4.57.3" | |
| } | |