Text Classification
Transformers
Safetensors
English
deberta-v2
deberta
sequence-classification
medicine
telerehabilitation
MeDeBERTa
MeDeBERTaBot
Instructions to use malakhovks/MeDeBERTa with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use malakhovks/MeDeBERTa with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="malakhovks/MeDeBERTa")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("malakhovks/MeDeBERTa") model = AutoModelForSequenceClassification.from_pretrained("malakhovks/MeDeBERTa", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download classification_report.csv from malakhovks/MeDeBERTa: direct link, hf CLI and curl.
- Browser
- Download file 1.45 kB
-
https://huggingface.co/malakhovks/MeDeBERTa/resolve/main/classification_report.csv
- Command line
-
hf download hf://malakhovks/MeDeBERTa/classification_report.csv
-
curl -L -o classification_report.csv https://huggingface.co/malakhovks/MeDeBERTa/resolve/main/classification_report.csv
1.45 kB
| ,precision,recall,f1-score,support | |
| any_code,1.0000,1.0000,1.0000,980.0000 | |
| any_icd,1.0000,1.0000,1.0000,950.0000 | |
| articles,1.0000,1.0000,1.0000,1022.0000 | |
| causes,1.0000,0.9990,0.9995,961.0000 | |
| certain cpt,1.0000,1.0000,1.0000,239.0000 | |
| certain g-code,1.0000,1.0000,1.0000,231.0000 | |
| certain hcpcs,1.0000,1.0000,1.0000,56.0000 | |
| certain icd 10,1.0000,1.0000,1.0000,918.0000 | |
| certain icd 9,1.0000,1.0000,1.0000,884.0000 | |
| contexts,0.9881,0.9870,0.9875,923.0000 | |
| contraindications precautions,1.0000,0.9990,0.9995,965.0000 | |
| cpt,1.0000,0.9990,0.9995,977.0000 | |
| description,0.9864,0.9931,0.9897,875.0000 | |
| diagnosis need for treatment,1.0000,0.9989,0.9995,940.0000 | |
| g-code,0.9968,1.0000,0.9984,939.0000 | |
| hcpcs,1.0000,0.9989,0.9995,947.0000 | |
| icd 10,1.0000,1.0000,1.0000,907.0000 | |
| icd 9,1.0000,0.9990,0.9995,954.0000 | |
| indicatons,0.9978,0.9946,0.9962,921.0000 | |
| pathogenesis,0.9979,0.9990,0.9985,970.0000 | |
| patient education,1.0000,1.0000,1.0000,961.0000 | |
| prognosis,0.9979,1.0000,0.9990,954.0000 | |
| references,1.0000,1.0000,1.0000,967.0000 | |
| reimbursement,0.9990,0.9990,0.9990,968.0000 | |
| relations,0.9968,0.9968,0.9968,952.0000 | |
| risk factors,1.0000,1.0000,1.0000,974.0000 | |
| rule out,1.0000,1.0000,1.0000,867.0000 | |
| symptoms,1.0000,0.9979,0.9990,975.0000 | |
| synonyms,0.9990,1.0000,0.9995,954.0000 | |
| test,0.9989,1.0000,0.9995,930.0000 | |
| treatment summary,1.0000,0.9978,0.9989,927.0000 | |
| accuracy,0.9986,0.9986,0.9986,0.9986 | |
| macro avg,0.9987,0.9987,0.9987,26988.0000 | |
| weighted avg,0.9986,0.9986,0.9986,26988.0000 | |