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:
- 5f7f8e483e21c7875cadc484f92f17dea671a61c88a8ea7270c9e9d81cd15296
- Size of remote file:
- 657 MB
- SHA256:
- 4c330a546c4f0428d6d0ad08cdf55e8e7dcd83983e3ad25606f74cc02c919fee
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