Text Classification
Transformers
PyTorch
TensorBoard
bert
Generated from Trainer
text-embeddings-inference
Instructions to use Amdalotaibi/bert-base-arabic-camelbert-da-traffics-topic-2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Amdalotaibi/bert-base-arabic-camelbert-da-traffics-topic-2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Amdalotaibi/bert-base-arabic-camelbert-da-traffics-topic-2")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Amdalotaibi/bert-base-arabic-camelbert-da-traffics-topic-2") model = AutoModelForSequenceClassification.from_pretrained("Amdalotaibi/bert-base-arabic-camelbert-da-traffics-topic-2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 03df2e951f95c33ad6955b835606e0ea63901dc8b5a314b86617f6ce1e45f818
- Size of remote file:
- 436 MB
- SHA256:
- 540453be1a7528feb1f7881bfe3df13cbb8bf4ce2cf0719b074b89d687535986
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