Text Classification
Transformers
TensorBoard
Safetensors
bert
Generated from Trainer
text-embeddings-inference
Instructions to use intermezzo672/NHS-dmis-binary with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use intermezzo672/NHS-dmis-binary with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="intermezzo672/NHS-dmis-binary", device_map="auto")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("intermezzo672/NHS-dmis-binary") model = AutoModelForSequenceClassification.from_pretrained("intermezzo672/NHS-dmis-binary", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 3ffebf24f7d85e7406daaf1e62a6aac5f1896caddbc7a12d25f75593b9ee3176
- Size of remote file:
- 4.92 kB
- SHA256:
- ab3c0161f4b663e8ad8f4a8e7b79e2f909256b84d9333819e6ef45935c4a7908
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