Instructions to use karths/binary_classification_train_requirement with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use karths/binary_classification_train_requirement with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="karths/binary_classification_train_requirement")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("karths/binary_classification_train_requirement") model = AutoModelForSequenceClassification.from_pretrained("karths/binary_classification_train_requirement", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- cf183a037c89de66c803b9708f50f9e82b952da26b52da2d002a70cf6b0f645c
- Size of remote file:
- 23.8 MB
- SHA256:
- 0cc1c649501a6cf87f7b064645b05d5cb8ae6b71052feb3f280af457e0ba80ef
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