Instructions to use Jrinky/classifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Jrinky/classifier with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Jrinky/classifier")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Jrinky/classifier") model = AutoModelForSequenceClassification.from_pretrained("Jrinky/classifier") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- e4d4e0ec46818d28b5ded4e2a4b9ac2b88d50eaba514b2bc5a438b93187b4d74
- Size of remote file:
- 433 MB
- SHA256:
- b73371d74a30c50f780b60cce7bcdc6a308b140f29d232de99cf09ee217ebb51
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