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", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- b1258531dd7d268d957b22675bca93ac22e2ddd401d8facde38e9a77b2803865
- Size of remote file:
- 5.84 kB
- SHA256:
- 8b806ca98f836fe6267505647fe8aef8f8b23d89b3d32d2f080403cf4a56df68
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