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
File size: 451 Bytes
decba57 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 | {
"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"
}
|