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wajidlinux99/gibberish-text-detector

sourceHugging Faceupdated 2y agoView on Hugging Face
6likes17kdownloads
Model Card

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