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:
- 58e2aca366447a1339cd51fc59b1a456a4225b2294679f714ebecb4ddcd9faa6
- Size of remote file:
- 657 MB
- SHA256:
- e756e3a928dd1c6c322db700a9ae85f875bab8edb2db23971e3a45cf02dd10e1
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