Text Classification
Transformers
TensorBoard
Safetensors
bert
Generated from Trainer
text-embeddings-inference
Instructions to use intermezzo672/NHS-binary-class with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use intermezzo672/NHS-binary-class with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="intermezzo672/NHS-binary-class")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("intermezzo672/NHS-binary-class") model = AutoModelForSequenceClassification.from_pretrained("intermezzo672/NHS-binary-class") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 1d24eb2898ae1a6c931d3156317d03ce84bc7d568f6d355c6c82ddfd78258df0
- Size of remote file:
- 438 MB
- SHA256:
- 98a33ce0ed4378275ab49f8e83ea579e2190e46aa2278b19174adbfcd265eee4
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