readme: ---
  tags: autonlp
  language: en
  widget:
  - text: "I love AutoNLP 🤗"
  datasets:
  - kSaluja/autonlp-data-tele_red_data_model
  co2_eq_emissions: 2.379476355147211
  ---
  
  # Model Trained Using AutoNLP
  
  - Problem type: Entity Extraction
  - Model ID: 585716433
  - CO2 Emissions (in grams): 2.379476355147211
  
  ## Validation Metrics
  
  - Loss: 0.15210922062397003
  - Accuracy: 0.9724770642201835
  - Precision: 0.950836820083682
  - Recall: 0.9625838333921638
  - F1: 0.9566742676723382
  
  ## 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/kSaluja/autonlp-tele_red_data_model-585716433
  ```
  
  Or Python API:
  
  ```
  from transformers import AutoModelForTokenClassification, AutoTokenizer
  
  model = AutoModelForTokenClassification.from_pretrained("kSaluja/autonlp-tele_red_data_model-585716433", use_auth_token=True)
  
  tokenizer = AutoTokenizer.from_pretrained("kSaluja/autonlp-tele_red_data_model-585716433", use_auth_token=True)
  
  inputs = tokenizer("I love AutoNLP", return_tensors="pt")
  
  outputs = model(**inputs)
  ```