Instructions to use InVoS/BERT_Sequence_Classification_Symptom_v2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use InVoS/BERT_Sequence_Classification_Symptom_v2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="InVoS/BERT_Sequence_Classification_Symptom_v2")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("InVoS/BERT_Sequence_Classification_Symptom_v2") model = AutoModelForSequenceClassification.from_pretrained("InVoS/BERT_Sequence_Classification_Symptom_v2") - Notebooks
- Google Colab
- Kaggle
| license: apache-2.0 | |
| datasets: | |
| - InVoS/Symptom_Text_Labels | |
| language: | |
| - en | |
| metrics: | |
| - accuracy | |
| base_model: | |
| - medicalai/ClinicalBERT | |
| pipeline_tag: text-classification | |
| library_name: transformers | |
| tags: | |
| - medical | |