readme: ---
  tags:
  - autotrain
  - text-classification
  language:
  - unk
  widget:
  - text: "Vull sentir una canço del Pets"
  - text: "Com puc anar a l'estació de trens?"
  - text: "afegeix a la llista de la compra un litre de llet"
  datasets:
  - crodri/autotrain-data-massive-4-catalan
  co2_eq_emissions:
    emissions: 13.789236303098791
  ---
  
  # Model Trained Using AutoTrain
  
  - Problem type: Multi-class Classification
  - Model ID: 2452075980
  - CO2 Emissions (in grams): 13.7892
  
  ## Validation Metrics
  
  - Loss: 0.546
  - Accuracy: 0.882
  - Macro F1: 0.855
  - Micro F1: 0.882
  - Weighted F1: 0.881
  - Macro Precision: 0.862
  - Micro Precision: 0.882
  - Weighted Precision: 0.886
  - Macro Recall: 0.858
  - Micro Recall: 0.882
  - Weighted Recall: 0.882
  
  
  ## 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/crodri/MassiveCatalanIntents
  ```
  
  Or Python API:
  
  ```
  from transformers import pipeline, AutoModelForSequenceClassification, AutoTokenizer
  
  tokenizer = AutoTokenizer.from_pretrained("crodri/MassiveCatalanIntents", use_auth_token=True)
  
  model = AutoModelForSequenceClassification.from_pretrained("crodri/MassiveCatalanIntents", use_auth_token=True)
  
  pipe = pipeline("text-classification",model=model,tokenizer=tokenizer)
  
  result = pipe("afegeix a la llista de la compra un litre de llet")
  ```