Text Classification
Transformers
Safetensors
distilbert
multi-label-classification
dental
medical
evidence-based-medicine
systematic-review
Eval Results (legacy)
text-embeddings-inference
Instructions to use Tuminha/dental-evidence-triage with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Tuminha/dental-evidence-triage with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Tuminha/dental-evidence-triage")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Tuminha/dental-evidence-triage") model = AutoModelForSequenceClassification.from_pretrained("Tuminha/dental-evidence-triage", device_map="auto") - Notebooks
- Google Colab
- Kaggle
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