README.md

metadata

tags: autonlp
language: en
widget:
  - text: I love AutoNLP 🤗
datasets:
  - sefaozalpadl/autonlp-data-election_relevancy_analysis
co2_eq_emissions: 1.3248523193990855

Model Trained Using AutoNLP

• Problem type: Binary Classification
• Model ID: 23315155
• CO2 Emissions (in grams): 1.3248523193990855

Validation Metrics

• Loss: 0.4240806996822357
• Accuracy: 0.8173913043478261
• Precision: 0.8837209302325582
• Recall: 0.8085106382978723
• AUC: 0.8882580285281696
• F1: 0.8444444444444444

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/sefaozalpadl/autonlp-election_relevancy_analysis-23315155

Or Python API:

from transformers import AutoModelForSequenceClassification, AutoTokenizer

model = AutoModelForSequenceClassification.from_pretrained("sefaozalpadl/autonlp-election_relevancy_analysis-23315155", use_auth_token=True)

tokenizer = AutoTokenizer.from_pretrained("sefaozalpadl/autonlp-election_relevancy_analysis-23315155", use_auth_token=True)

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

outputs = model(**inputs)