Instructions to use Jeevesh8/std_pnt_04_feather_berts-21 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-21 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-21")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Jeevesh8/std_pnt_04_feather_berts-21") model = AutoModelForSequenceClassification.from_pretrained("Jeevesh8/std_pnt_04_feather_berts-21") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 0eb1f3ed29245982473630a2c42bdc91e17f95b0c4c0d786ebbe8fa9bce3dca7
- Size of remote file:
- 438 MB
- SHA256:
- df3d5c76c5008e6d1ec9e35d331c78c4e4c8b4628db122db92f810653cdf57d1
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