README.md

metadata

tags:
  - autotrain
  - token-classification
  - medical
language:
  - fr
widget:
  - text: Prendré 2 compris par jour, pendant 1 mois.
  - text: DOLIPRANETABS 1000 MG CPR PELL PLQ/8 (Paracétamol 1.000mg comprimé)
datasets:
  - Posos/MedNERF
co2_eq_emissions:
  emissions: 0.11647938304211661
license: mit
metrics:
  - f1
  - accuracy
  - precision
  - recall

Model Trained Using AutoTrain

• Problem type: Entity Extraction
• Model ID: 69856137957
• CO2 Emissions (in grams): 0.1165

Validation Metrics

• Loss: 1.510
• Accuracy: 0.706
• Precision: 0.648
• Recall: 0.679
• F1: 0.663

Usage

You can use cURL to access this model:

$ curl -X POST -H "Authorization: Bearer YOUR_API_KEY" -H "Content-Type: application/json" -d '{"inputs": "I love AutoTrain"}' https://api-inference.huggingface.co/models/davanstrien/autotrain-french-ner-blank-model-69856137957

Or Python API:

from transformers import AutoModelForTokenClassification, AutoTokenizer

model = AutoModelForTokenClassification.from_pretrained("davanstrien/autotrain-french-ner-blank-model-69856137957", use_auth_token=True)

tokenizer = AutoTokenizer.from_pretrained("davanstrien/autotrain-french-ner-blank-model-69856137957", use_auth_token=True)

inputs = tokenizer("I love AutoTrain", return_tensors="pt")

outputs = model(**inputs)