Text Classification
Transformers
PyTorch
Enawené-Nawé
bert
Trained with AutoTrain
text-embeddings-inference
Instructions to use MMars/arabertv2_flodusta with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use MMars/arabertv2_flodusta with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="MMars/arabertv2_flodusta")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("MMars/arabertv2_flodusta") model = AutoModelForSequenceClassification.from_pretrained("MMars/arabertv2_flodusta") - Notebooks
- Google Colab
- Kaggle
Adding `safetensors` variant of this model
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by SFconvertbot - opened
- model.safetensors +3 -0
model.safetensors
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version https://git-lfs.github.com/spec/v1
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oid sha256:851bae3442634d92a1989d1e8b55ac8eb792713914fd622e874f8eb2cf1f0535
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size 540813416
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