Instructions to use connectivity/feather_berts_6 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use connectivity/feather_berts_6 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="connectivity/feather_berts_6")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("connectivity/feather_berts_6") model = AutoModelForSequenceClassification.from_pretrained("connectivity/feather_berts_6") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 6f4c631177ea1993ec1e4f4a2394a052c68d327fed2b62f45671b8719e66f6e3
- Size of remote file:
- 438 MB
- SHA256:
- 3c8d546270a0b48d11537f4c64cc92296e88bd6e0ebc6bc5c35f42cc918eda7e
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