Instructions to use zhernosek12/classif_sasha with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use zhernosek12/classif_sasha with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="zhernosek12/classif_sasha")# Load model directly from transformers import AutoProcessor, AutoModelForSequenceClassification processor = AutoProcessor.from_pretrained("zhernosek12/classif_sasha") model = AutoModelForSequenceClassification.from_pretrained("zhernosek12/classif_sasha", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 7ff4681ef674d6b558d34680fe597f0ea777674a99480b7204a7f095fca873ea
- Size of remote file:
- 802 MB
- SHA256:
- cb5ef9dbf9d75683f8e13bb846b820395a65686a2391d4709b7bb74b6ddcaf0c
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