README.md

metadata

tags: autotrain
language: unk
widget:
  - text: I love AutoTrain 🤗
datasets:
  - borgr/autotrain-data-Trial
co2_eq_emissions: 16.050883703347175

Model Trained Using AutoTrain

• Problem type: Binary Classification
• Model ID: 1053836318
• CO2 Emissions (in grams): 16.050883703347175

Validation Metrics

• Loss: 0.15769560635089874
• Accuracy: 0.9472160356347439
• Precision: 0.9516664453591821
• Recall: 0.9538195368645196
• AUC: 0.9851485979250193
• F1: 0.9527417746759722

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-1053836318

Or Python API:

from transformers import AutoModelForSequenceClassification, AutoTokenizer

model = AutoModelForSequenceClassification.from_pretrained("borgr/autotrain-Trial-1053836318", use_auth_token=True)

tokenizer = AutoTokenizer.from_pretrained("borgr/autotrain-Trial-1053836318", use_auth_token=True)

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

outputs = model(**inputs)