Instructions to use connectivity/feather_berts_70 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use connectivity/feather_berts_70 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="connectivity/feather_berts_70")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("connectivity/feather_berts_70") model = AutoModelForSequenceClassification.from_pretrained("connectivity/feather_berts_70") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 071737e6100cde3a949d56a9a83d2060eedbe54642bb990115e5a5995206d3e2
- Size of remote file:
- 12.1 MB
- SHA256:
- f3ace9953a719efe22b6f924c616853f7174945e9afd6c7376cdd837f56a989e
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