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")# 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:
- fbccb13aa40632d5b37fbb067d15b9c65161b3337a134f0b71c04df7087760eb
- Size of remote file:
- 433 MB
- SHA256:
- 866d942fc37e4f0fb426378bf1c6eb924c534579565114a87d6e7be874dddaca
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