readme: ---
  language:
  - en
  pipeline_tag: text-classification
  tags:
  - text
  - nlp
  - correction
  ---
  
  
  # Model Trained Using AutoNLP
  
  - Problem type: Multi-class Classification
  - Model ID: 492513457
  - CO2 Emissions (in grams): 5.527544460835904
  
  ## Validation Metrics
  
  - Loss: 0.07609463483095169
  - Accuracy: 0.9735624586913417
  - Macro F1: 0.9736173135739408
  - Micro F1: 0.9735624586913417
  - Weighted F1: 0.9736173135739408
  - Macro Precision: 0.9737771415197378
  - Micro Precision: 0.9735624586913417
  - Weighted Precision: 0.9737771415197378
  - Macro Recall: 0.9735624586913417
  - Micro Recall: 0.9735624586913417
  - Weighted Recall: 0.9735624586913417
  
  
  ## 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": "Is this text really worth it?"}' https://api-inference.huggingface.co/models/wajidlinux99/gibberish-text-detector
  ```
  
  Or Python API:
  
  ```
  from transformers import AutoModelForSequenceClassification, AutoTokenizer
  
  model = AutoModelForSequenceClassification.from_pretrained("wajidlinux99/gibberish-text-detector", use_auth_token=True)
  
  tokenizer = AutoTokenizer.from_pretrained("wajidlinux99/gibberish-text-detector", use_auth_token=True)
  
  inputs = tokenizer("Is this text really worth it?", return_tensors="pt")
  
  outputs = model(**inputs)
  ```
  
  # Original Repository
  
  ***madhurjindal/autonlp-Gibberish-Detector-492513457