Instructions to use CIS5190ml/bert4 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use CIS5190ml/bert4 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="CIS5190ml/bert4")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("CIS5190ml/bert4") model = AutoModelForSequenceClassification.from_pretrained("CIS5190ml/bert4", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 13271db8c853b78426f491c205008d157b510a080d1f5ba11f820beed66d5007
- Size of remote file:
- 5.24 kB
- SHA256:
- bc2aef91a14ec4f2f705d1b67cf5f8c0270bd126a667573224537b6f8aaa6967
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