readme: ---
  tags: autonlp
  language: unk
  widget:
  - text: "I love AutoNLP 🤗"
  datasets:
  - doctorlan/autonlp-data-ctrip
  co2_eq_emissions: 24.879856894708393
  ---
  
  # Model Trained Using AutoNLP
  
  - Problem type: Binary Classification
  - Model ID: 653519223
  - CO2 Emissions (in grams): 24.879856894708393
  
  ## Validation Metrics
  
  - Loss: 0.14671853184700012
  - Accuracy: 0.9676666666666667
  - Precision: 0.9794159885112494
  - Recall: 0.9742857142857143
  - AUC: 0.9901396825396825
  - F1: 0.9768441155407017
  
  ## 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/doctorlan/autonlp-ctrip-653519223
  ```
  
  Or Python API:
  
  ```
  from transformers import AutoModelForSequenceClassification, AutoTokenizer
  
  model = AutoModelForSequenceClassification.from_pretrained("doctorlan/autonlp-ctrip-653519223", use_auth_token=True)
  
  tokenizer = AutoTokenizer.from_pretrained("doctorlan/autonlp-ctrip-653519223", use_auth_token=True)
  
  inputs = tokenizer("I love AutoNLP", return_tensors="pt")
  
  outputs = model(**inputs)
  ```