Instructions to use karths/binary_classification_train_people with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use karths/binary_classification_train_people with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="karths/binary_classification_train_people")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("karths/binary_classification_train_people") model = AutoModelForSequenceClassification.from_pretrained("karths/binary_classification_train_people", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 066cdb66f09658b4d508b4ca1164a7507c8aaefe47cb01e8b3475e46323f8dc9
- Size of remote file:
- 4.66 kB
- SHA256:
- 2c65e0c0edc022b050dfc334823aef6e68555b7a207e18ab2f45ea6ae3bb7584
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