Instructions to use MayBashendy/Arabic_CrossPrompt_FineTuningAraBERT_noAug_TestTask4_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_TestTask4_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_TestTask4_development")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("MayBashendy/Arabic_CrossPrompt_FineTuningAraBERT_noAug_TestTask4_development") model = AutoModelForSequenceClassification.from_pretrained("MayBashendy/Arabic_CrossPrompt_FineTuningAraBERT_noAug_TestTask4_development", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 2932f8cae20fabb877b69d1ca7c481769a5bc920eb131a02015e1408e402ebe3
- Size of remote file:
- 541 MB
- SHA256:
- 2eb271ad0c1a2a1905642f179d9cff1850034fddb7ecf79f765820c8df23a082
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