Instructions to use MayBashendy/Arabic_CrossPrompt_FineTuningAraBERT_noAug_TestTask5_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_TestTask5_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_TestTask5_development")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("MayBashendy/Arabic_CrossPrompt_FineTuningAraBERT_noAug_TestTask5_development") model = AutoModelForSequenceClassification.from_pretrained("MayBashendy/Arabic_CrossPrompt_FineTuningAraBERT_noAug_TestTask5_development", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- b85439f779f7f0e989f575e2431366ec7e660782edc14e6594c0542486b0de4e
- Size of remote file:
- 541 MB
- SHA256:
- e0f0b55ea7f11a3caee958948af943db40709aa63b316f9896fd5a7f86450881
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