Instructions to use connectivity/feather_berts_98 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use connectivity/feather_berts_98 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="connectivity/feather_berts_98")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("connectivity/feather_berts_98") model = AutoModelForSequenceClassification.from_pretrained("connectivity/feather_berts_98") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- a45e2cd701703f7ab18e1799c5735c58bf30acf0da2d1fea613a07f927865309
- Size of remote file:
- 438 MB
- SHA256:
- c0975bdc06fc28762e5f1bacec4a1c1f884d30e1eb8205bad9d1705eaf77532e
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