Text Classification
Transformers
PyTorch
Safetensors
English
bert
medical
symptomchecker
nlp
healthcare
text-embeddings-inference
Instructions to use Lech-Iyoko/bert-symptom-checker with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Lech-Iyoko/bert-symptom-checker with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Lech-Iyoko/bert-symptom-checker")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Lech-Iyoko/bert-symptom-checker") model = AutoModelForSequenceClassification.from_pretrained("Lech-Iyoko/bert-symptom-checker") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 3cb38ffa86f8a4e90fa3d526292f3ba0f083c94f68f574bffc441c21be6f61fb
- Size of remote file:
- 438 MB
- SHA256:
- 83caff0d8d6c035031243c434036f60a3e1e7a246840e83de0a2afcba33a5844
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