Instructions to use Amani123/classifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Amani123/classifier with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Amani123/classifier")# Load model directly from transformers import AutoProcessor, AutoModelForSequenceClassification processor = AutoProcessor.from_pretrained("Amani123/classifier") model = AutoModelForSequenceClassification.from_pretrained("Amani123/classifier") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 2be900130c2e3c7ed7a3448e051d32f9c7d5e258449c4cea99239aee18d86498
- Size of remote file:
- 802 MB
- SHA256:
- 900abfd211566f83971e429f798d1aec9e9bda8cd033c4accd43971a228aaf98
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