Instructions to use yabramuvdi/bert-sector with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use yabramuvdi/bert-sector with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="yabramuvdi/bert-sector")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("yabramuvdi/bert-sector") model = AutoModelForSequenceClassification.from_pretrained("yabramuvdi/bert-sector") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- c62b745ca26c2526d1aa08e1ce1983201f88370bf57c6ac36d3fe6c015ce0bf7
- Size of remote file:
- 438 MB
- SHA256:
- 498fd663014ca2a00b7d64410eed29c5e7ee5db37db79ff497be0f1047e8e0e4
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