README.md

metadata

tags: autonlp
language: en
widget:
  - text: I love AutoNLP 🤗
datasets:
  - MadhurJindalWorkMail/autonlp-data-Gibb-Detect
co2_eq_emissions: 70.95647633212745

Model Trained Using AutoNLP

• Problem type: Multi-class Classification
• Model ID: 515314387
• CO2 Emissions (in grams): 70.95647633212745

Validation Metrics

• Loss: 0.08077705651521683
• Accuracy: 0.9760103738923709
• Macro F1: 0.9728412857204902
• Micro F1: 0.9760103738923709
• Weighted F1: 0.9759907151741426
• Macro Precision: 0.9736622407675567
• Micro Precision: 0.9760103738923709
• Weighted Precision: 0.97673611876005
• Macro Recall: 0.9728978421381711
• Micro Recall: 0.9760103738923709
• Weighted Recall: 0.9760103738923709

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/MadhurJindalWorkMail/autonlp-Gibb-Detect-515314387

Or Python API:

from transformers import AutoModelForSequenceClassification, AutoTokenizer

model = AutoModelForSequenceClassification.from_pretrained("MadhurJindalWorkMail/autonlp-Gibb-Detect-515314387", use_auth_token=True)

tokenizer = AutoTokenizer.from_pretrained("MadhurJindalWorkMail/autonlp-Gibb-Detect-515314387", use_auth_token=True)

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

outputs = model(**inputs)