Instructions to use connectivity/feather_berts_42 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use connectivity/feather_berts_42 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="connectivity/feather_berts_42")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("connectivity/feather_berts_42") model = AutoModelForSequenceClassification.from_pretrained("connectivity/feather_berts_42") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 80fd41574f5f282c5fb81225d148c832d78f2d6eff23874e24f175aee6997046
- Size of remote file:
- 438 MB
- SHA256:
- 775ec23a9de41968158a8a05bd3456d31ff6baecca84aae7e099a539db90aaa6
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