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---
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)
``` |