README.md

metadata

tags: autonlp
language: en
widget:
  - text: I love AutoNLP 🤗
datasets:
  - zwang199/autonlp-data-traffic_nlp_binary
co2_eq_emissions: 1.171798205242445

Model Trained Using AutoNLP

• Problem type: Binary Classification
• Model ID: 537215209
• CO2 Emissions (in grams): 1.171798205242445

Validation Metrics

• Loss: 0.3879534602165222
• Accuracy: 0.8597449908925319
• Precision: 0.8318042813455657
• Recall: 0.9251700680272109
• AUC: 0.9230158730158731
• F1: 0.8760064412238325

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/zwang199/autonlp-traffic_nlp_binary-537215209

Or Python API:

from transformers import AutoModelForSequenceClassification, AutoTokenizer

model = AutoModelForSequenceClassification.from_pretrained("zwang199/autonlp-traffic_nlp_binary-537215209", use_auth_token=True)

tokenizer = AutoTokenizer.from_pretrained("zwang199/autonlp-traffic_nlp_binary-537215209", use_auth_token=True)

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

outputs = model(**inputs)