readme: ---
  tags: autonlp
  language: fr
  widget:
  - text: "I love AutoNLP 🤗"
  datasets:
  - medA/autonlp-data-FR_another_test
  co2_eq_emissions: 70.54639641012226
  ---
  
  # Model Trained Using AutoNLP
  
  - Problem type: Multi-class Classification
  - Model ID: 565016091
  - CO2 Emissions (in grams): 70.54639641012226
  
  ## Validation Metrics
  
  - Loss: 0.5170354247093201
  - Accuracy: 0.8545909432074056
  - Macro F1: 0.7910662503820883
  - Micro F1: 0.8545909432074056
  - Weighted F1: 0.8539837213761081
  - Macro Precision: 0.8033640381948799
  - Micro Precision: 0.8545909432074056
  - Weighted Precision: 0.856160322286008
  - Macro Recall: 0.7841845637031052
  - Micro Recall: 0.8545909432074056
  - Weighted Recall: 0.8545909432074056
  
  
  ## 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 AutoNLP"}' https://api-inference.huggingface.co/models/medA/autonlp-FR_another_test-565016091
  ```
  
  Or Python API:
  
  ```
  from transformers import AutoModelForSequenceClassification, AutoTokenizer
  
  model = AutoModelForSequenceClassification.from_pretrained("medA/autonlp-FR_another_test-565016091", use_auth_token=True)
  
  tokenizer = AutoTokenizer.from_pretrained("medA/autonlp-FR_another_test-565016091", use_auth_token=True)
  
  inputs = tokenizer("I love AutoNLP", return_tensors="pt")
  
  outputs = model(**inputs)
  ```