Instructions to use SMG0/Model4_arabertv2_base_T1_WS_A100_2nd_F1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use SMG0/Model4_arabertv2_base_T1_WS_A100_2nd_F1 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="SMG0/Model4_arabertv2_base_T1_WS_A100_2nd_F1")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("SMG0/Model4_arabertv2_base_T1_WS_A100_2nd_F1") model = AutoModelForSequenceClassification.from_pretrained("SMG0/Model4_arabertv2_base_T1_WS_A100_2nd_F1") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- aa52ddbc8e5a06568eb677d7fca39496df47c8b0df4134f93cdfe83d296f501e
- Size of remote file:
- 541 MB
- SHA256:
- 8948828d83dcd645cd54d446c5cc5bd874d57e5df97a8f500feb6032ebf0c657
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