Text Classification
Transformers
PyTorch
Arabic
bert
Trained with AutoTrain
text-embeddings-inference
Instructions to use MMars/marbertv2_flodusta with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use MMars/marbertv2_flodusta with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="MMars/marbertv2_flodusta")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("MMars/marbertv2_flodusta") model = AutoModelForSequenceClassification.from_pretrained("MMars/marbertv2_flodusta") - Notebooks
- Google Colab
- Kaggle
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README.md
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# Labels Mapping
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0 non event
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1 flood
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2 dust storm
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3 traffic accident
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# Model Trained Using AutoTrain
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- Problem type: Multi-class Classification
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---
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# Labels Mapping
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0 non event
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1 flood
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2 dust storm
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3 traffic accident
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# Model Trained Using AutoTrain
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- Problem type: Multi-class Classification
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