Instructions to use akadhim-ai/bert_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use akadhim-ai/bert_model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="akadhim-ai/bert_model")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("akadhim-ai/bert_model") model = AutoModelForSequenceClassification.from_pretrained("akadhim-ai/bert_model") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 1caca28c94ea8ca83ae1794a44897f06a2fc4018f1dec7cada18f6da8819d048
- Size of remote file:
- 3.31 kB
- SHA256:
- 178cb1d1d535b352bda3a2fa6e8d16c3fd8611c8ca751cd40874ef396440743d
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