Instructions to use connectivity/feather_berts_44 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use connectivity/feather_berts_44 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="connectivity/feather_berts_44")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("connectivity/feather_berts_44") model = AutoModelForSequenceClassification.from_pretrained("connectivity/feather_berts_44") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 64e7c4eb6d7bd5461a3b3aa7fd82ebcc4a52810280f39b00cdef74bd00234981
- Size of remote file:
- 438 MB
- SHA256:
- b722be9a2b9c314af254429fb61024abe92c741ec59f37afd94e9c595a32e32b
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