Text Classification
Transformers
Safetensors
bert
Arabic
Dialect Identification
Multi-Label
BERT
MLADI
NLP
text-embeddings-inference
Instructions to use AHAAM/B2BERT with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use AHAAM/B2BERT with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="AHAAM/B2BERT")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("AHAAM/B2BERT") model = AutoModelForSequenceClassification.from_pretrained("AHAAM/B2BERT", device_map="auto") - Notebooks
- Google Colab
- Kaggle
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# Model Card for
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## Model Details
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- **Model type:** Transformer-based multi-label classifier
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- **Language(s) (NLP):** Arabic (Dialectal Variants)
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- **License:** TBD
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- **Finetuned from model:** CAMeLBERT
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## Bias, Risks, and Limitations
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tags: []
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# Model Card for B2BERT
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## Model Details
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- **Model type:** Transformer-based multi-label classifier
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- **Language(s) (NLP):** Arabic (Dialectal Variants)
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- **License:** TBD
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- **Finetuned from model:** CAMeLBERT
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## Bias, Risks, and Limitations
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