readme: ---
  tags: autotrain
  language: en
  widget:
  - text: "Bill Gates wants to use mass Covid-19 vaccination campaign to implant microchips to track people"
  
  datasets:
  - Fake and real news datasets by CLÉMENT BISAILLON
  co2_eq_emissions: 4.415122243239347
  ---
  
  # Model Trained Using AutoTrain
  
  - Problem: Fake News Classification
  - Problem type: Binary Classification
  - Model ID: 785124234
  - CO2 Emissions (in grams): 4.415122243239347
  
  ## Validation Metrics
  
  - Loss: 0.00012586714001372457
  - Accuracy: 0.9998886538247411
  - Precision: 1.0
  - Recall: 0.9997665732959851
  - AUC: 0.9999999999999999
  - F1: 0.999883273024396
  
  ## 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/Nithiwat/autotrain-fake-news-classifier-785124234
  ```
  
  Or Python API:
  
  ```
  from transformers import AutoModelForSequenceClassification, AutoTokenizer
  
  model = AutoModelForSequenceClassification.from_pretrained("Nithiwat/autotrain-fake-news-classifier-785124234", use_auth_token=True)
  
  tokenizer = AutoTokenizer.from_pretrained("Nithiwat/autotrain-fake-news-classifier-785124234", use_auth_token=True)
  
  inputs = tokenizer("I love AutoTrain", return_tensors="pt")
  
  outputs = model(**inputs)
  ```