Instructions to use MayBashendy/Arabic_CrossPrompt_FineTuningAraBERT_noAug_TestTask8_development with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use MayBashendy/Arabic_CrossPrompt_FineTuningAraBERT_noAug_TestTask8_development with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="MayBashendy/Arabic_CrossPrompt_FineTuningAraBERT_noAug_TestTask8_development")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("MayBashendy/Arabic_CrossPrompt_FineTuningAraBERT_noAug_TestTask8_development") model = AutoModelForSequenceClassification.from_pretrained("MayBashendy/Arabic_CrossPrompt_FineTuningAraBERT_noAug_TestTask8_development", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 5b141f6232cd3d7a9e7a3ac295b5a960184032da0c527e1af05bc43e8e50d5a7
- Size of remote file:
- 541 MB
- SHA256:
- 017c4f66e17364ba04eafc7a12d8289007cf69cad3fc71b72339d0968824f810
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