README.md

metadata

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")