README.md

metadata

tags: autotrain
language: unk
widget:
  - text: I love AutoTrain 🤗
datasets:
  - borgr/autotrain-data-Trial
co2_eq_emissions: 21.05202945092033

Model Trained Using AutoTrain

• Problem type: Binary Classification
• Model ID: 1053836319
• CO2 Emissions (in grams): 21.05202945092033

Validation Metrics

• Loss: 0.1608610451221466
• Accuracy: 0.9461024498886415
• Precision: 0.956428187197418
• Recall: 0.9464998669150918
• AUC: 0.9843301458499762
• F1: 0.9514381270903011

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/borgr/autotrain-Trial-1053836319

Or Python API:

from transformers import AutoModelForSequenceClassification, AutoTokenizer

model = AutoModelForSequenceClassification.from_pretrained("borgr/autotrain-Trial-1053836319", use_auth_token=True)

tokenizer = AutoTokenizer.from_pretrained("borgr/autotrain-Trial-1053836319", use_auth_token=True)

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

outputs = model(**inputs)