Instructions to use Jeevesh8/std_pnt_04_feather_berts-13 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Jeevesh8/std_pnt_04_feather_berts-13 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Jeevesh8/std_pnt_04_feather_berts-13")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Jeevesh8/std_pnt_04_feather_berts-13") model = AutoModelForSequenceClassification.from_pretrained("Jeevesh8/std_pnt_04_feather_berts-13") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 57259219d78829a8ff3b3e2b0133d9c8df029edf34e1c4d999382313048bf88d
- Size of remote file:
- 438 MB
- SHA256:
- 3e9a68f7c7d9cf2029236410702c7db731347dcad94c0971c70621390d5482e9
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