README.md

metadata

tags: autonlp
language: en
widget:
  - text: I love AutoNLP 🤗
datasets:
  - madhurjindal/autonlp-data-Gibberish-Detector
co2_eq_emissions: 5.527544460835904

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": "I love AutoNLP"}' https://api-inference.huggingface.co/models/madhurjindal/autonlp-Gibberish-Detector-492513457

Or Python API:

from transformers import AutoModelForSequenceClassification, AutoTokenizer

model = AutoModelForSequenceClassification.from_pretrained("madhurjindal/autonlp-Gibberish-Detector-492513457", use_auth_token=True)

tokenizer = AutoTokenizer.from_pretrained("madhurjindal/autonlp-Gibberish-Detector-492513457", use_auth_token=True)

inputs = tokenizer("I love AutoNLP", return_tensors="pt")

outputs = model(**inputs)