Instructions to use spyn4ch/bert-binary-clf with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use spyn4ch/bert-binary-clf with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="spyn4ch/bert-binary-clf")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("spyn4ch/bert-binary-clf") model = AutoModelForSequenceClassification.from_pretrained("spyn4ch/bert-binary-clf") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- e6063991edf7b8be09d4f321fb98359277ccf8501699e44adef0ff7480184027
- Size of remote file:
- 438 MB
- SHA256:
- c31c022ae01b59a542a90244bc5f6364cc308868bc08ccae6b26cc56ce5ab52c
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