Instructions to use karths/binary_classification_train_perf with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use karths/binary_classification_train_perf with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="karths/binary_classification_train_perf")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("karths/binary_classification_train_perf") model = AutoModelForSequenceClassification.from_pretrained("karths/binary_classification_train_perf") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 38671bcaa2aa9bda3491d624f8ae660d513257e811834f757ed3a7deab82fb36
- Size of remote file:
- 4.66 kB
- SHA256:
- 6a94b4b803d070cd5ffa41baf23fe79d8a03c0d5b136cdeb16e47f54c88d1eeb
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