Instructions to use connectivity/feather_berts_76 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use connectivity/feather_berts_76 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="connectivity/feather_berts_76")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("connectivity/feather_berts_76") model = AutoModelForSequenceClassification.from_pretrained("connectivity/feather_berts_76") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 27eea9e6a69b1f654696d7659512f7963d1c2840179168377d1a7fcfa3091dfd
- Size of remote file:
- 438 MB
- SHA256:
- b73182edfbd91c4cfde041aff4e56d4bc71aca966055c5f456f2bf95c4514278
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