Instructions to use MayBashendy/Arabic_CrossPrompt_FineTuningAraBERT_noAug_TestTask7_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_TestTask7_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_TestTask7_development")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("MayBashendy/Arabic_CrossPrompt_FineTuningAraBERT_noAug_TestTask7_development") model = AutoModelForSequenceClassification.from_pretrained("MayBashendy/Arabic_CrossPrompt_FineTuningAraBERT_noAug_TestTask7_development", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- ee17d825b0931c254fb4847efc5a391f575a2453fff1634c66209ce2655ea667
- Size of remote file:
- 541 MB
- SHA256:
- aa28aef4390dd35371cf47d8dedea2cd3e563691b11452f052b568d6e02b57eb
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