README.md

metadata

tags:
  - autotrain
  - text-classification
language:
  - en
widget:
  - text: I love AutoTrain 🤗
datasets:
  - Kaludi/autotrain-data-reviews-sentiment-analysis
co2_eq_emissions:
  emissions: 24.76716845191504

Model Trained Using AutoTrain

• Problem type: Binary Classification
• Model ID: 3125888400
• CO2 Emissions (in grams): 24.7672

Validation Metrics

• Loss: 0.159
• Accuracy: 0.952
• Precision: 0.965
• Recall: 0.938
• AUC: 0.988
• F1: 0.951

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/Kaludi/autotrain-reviews-sentiment-analysis-3125888400

Or Python API:

from transformers import AutoModelForSequenceClassification, AutoTokenizer

model = AutoModelForSequenceClassification.from_pretrained("Kaludi/autotrain-reviews-sentiment-analysis-3125888400", use_auth_token=True)

tokenizer = AutoTokenizer.from_pretrained("Kaludi/autotrain-reviews-sentiment-analysis-3125888400", use_auth_token=True)

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

outputs = model(**inputs)