README.md

metadata

tags: autotrain
language: en
widget:
  - text: I love AutoTrain 🤗
datasets:
  - tayyaba/autotrain-data-pan
co2_eq_emissions: 27.081173251466467

Model Trained Using AutoTrain

• Problem type: Binary Classification
• Model ID: 977432399
• CO2 Emissions (in grams): 27.081173251466467

Validation Metrics

• Loss: 0.277687668800354
• Accuracy: 0.8841666666666667
• Precision: 0.9185918591859186
• Recall: 0.9277777777777778
• AUC: 0.9422805555555556
• F1: 0.9231619679380874

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 AutoTrain"}' https://api-inference.huggingface.co/models/tayyaba/autotrain-pan-977432399

Or Python API:

from transformers import AutoModelForSequenceClassification, AutoTokenizer

model = AutoModelForSequenceClassification.from_pretrained("tayyaba/autotrain-pan-977432399", use_auth_token=True)

tokenizer = AutoTokenizer.from_pretrained("tayyaba/autotrain-pan-977432399", use_auth_token=True)

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

outputs = model(**inputs)