readme: ---
  tags:
  - autotrain
  - text-classification
  language:
  - en
  widget:
  - text: "I love AutoTrain 🤗"
  datasets:
  - jawadhussein462/autotrain-data-neurips_chanllenge
  co2_eq_emissions:
    emissions: 25.138742530638098
  ---
  
  # Model Trained Using AutoTrain
  
  - Problem type: Binary Classification
  - Model ID: 1287149282
  - CO2 Emissions (in grams): 25.1387
  
  ## Validation Metrics
  
  - Loss: 0.272
  - Accuracy: 0.911
  - Precision: 0.733
  - Recall: 0.494
  - AUC: 0.823
  - F1: 0.591
  
  ## 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/jawadhussein462/autotrain-neurips_chanllenge-1287149282
  ```
  
  Or Python API:
  
  ```
  from transformers import AutoModelForSequenceClassification, AutoTokenizer
  
  model = AutoModelForSequenceClassification.from_pretrained("jawadhussein462/autotrain-neurips_chanllenge-1287149282", use_auth_token=True)
  
  tokenizer = AutoTokenizer.from_pretrained("jawadhussein462/autotrain-neurips_chanllenge-1287149282", use_auth_token=True)
  
  inputs = tokenizer("I love AutoTrain", return_tensors="pt")
  
  outputs = model(**inputs)
  ```