readme: ---
  tags: autonlp
  language: unk
  widget:
  - text: "I love AutoNLP 🤗"
  datasets:
  - Qinghui/autonlp-data-fake-covid-news
  co2_eq_emissions: 23.42719853096565
  ---
  
  # Model Trained Using AutoNLP
  
  - Problem type: Binary Classification
  - Model ID: 36769078
  - CO2 Emissions (in grams): 23.42719853096565
  
  ## Validation Metrics
  
  - Loss: 0.15959647297859192
  - Accuracy: 0.9817757009345794
  - Precision: 0.980411361410382
  - Recall: 0.9813725490196078
  - AUC: 0.9982379201680672
  - F1: 0.9808917197452229
  
  ## 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/Qinghui/autonlp-fake-covid-news-36769078
  ```
  
  Or Python API:
  
  ```
  from transformers import AutoModelForSequenceClassification, AutoTokenizer
  
  model = AutoModelForSequenceClassification.from_pretrained("Qinghui/autonlp-fake-covid-news-36769078", use_auth_token=True)
  
  tokenizer = AutoTokenizer.from_pretrained("Qinghui/autonlp-fake-covid-news-36769078", use_auth_token=True)
  
  inputs = tokenizer("I love AutoNLP", return_tensors="pt")
  
  outputs = model(**inputs)
  ```