readme: ---
  tags: xerox
  language: es
  widget:
  - text: "Debo de levantarme temprano para hacer ejercicio"
  datasets:
  - erixxdp/autotrain-data-gsemodel
  co2_eq_emissions: 0.027846282970913613
  ---
  
  # Model Trained Using AutoTrain
  
  - Problem type: Multi-class Classification
  - Model ID: 1148842296
  - CO2 Emissions (in grams): 0.027846282970913613
  
  ## Validation Metrics
  
  - Loss: 0.4816772937774658
  - Accuracy: 0.864
  - Macro F1: 0.865050349743783
  - Micro F1: 0.864
  - Weighted F1: 0.865050349743783
  - Macro Precision: 0.8706266090178479
  - Micro Precision: 0.864
  - Weighted Precision: 0.8706266090178482
  - Macro Recall: 0.864
  - Micro Recall: 0.864
  - Weighted Recall: 0.864
  
  
  ## 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/erixxdp/autotrain-gsemodel-1148842296
  ```
  
  Or Python API:
  
  ```
  from transformers import AutoModelForSequenceClassification, AutoTokenizer
  
  model = AutoModelForSequenceClassification.from_pretrained("erixxdp/autotrain-gsemodel-1148842296", use_auth_token=True)
  
  tokenizer = AutoTokenizer.from_pretrained("erixxdp/autotrain-gsemodel-1148842296", use_auth_token=True)
  
  inputs = tokenizer("I love AutoTrain", return_tensors="pt")
  
  outputs = model(**inputs)
  ```