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:
- 21917fd3221dd376cfdebf892290fcdcbcc5c8456f317c2871d5f0c3235dbe86
- Size of remote file:
- 12.1 MB
- SHA256:
- f18d50c657dcc4600913cd1d664a147c8bbab4c19857598a15b1c46034ee8cd7
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