Instructions to use SMG0/Model4_arabertv2_base_T2_WS_A100 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use SMG0/Model4_arabertv2_base_T2_WS_A100 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="SMG0/Model4_arabertv2_base_T2_WS_A100")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("SMG0/Model4_arabertv2_base_T2_WS_A100") model = AutoModelForSequenceClassification.from_pretrained("SMG0/Model4_arabertv2_base_T2_WS_A100", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 76220a1b157462c34c4c87bf7505109c67d72e7c7c9ba1aa13d6dbd4ddf3753e
- Size of remote file:
- 4.03 kB
- SHA256:
- 99aa69f7feabb7273e7ebf810c7c5a5aaaaceb75ffa6775c792c10ec6c9b3781
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