Instructions to use VCNC/bert_3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use VCNC/bert_3 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="VCNC/bert_3")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("VCNC/bert_3") model = AutoModelForSequenceClassification.from_pretrained("VCNC/bert_3", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 6b052ce280b63f8bcca6bae163d6a42291a35b73491ffc06f1b0035038abebff
- Size of remote file:
- 4.03 kB
- SHA256:
- 27c789d0418ee6bbca5a866a1a7972ec1aec00bdd3ee2cbcfa96632859a2ef89
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