README.md

metadata

tags:
  - autotrain
  - text-classification
language:
  - zh
widget:
  - text: I love AutoTrain 🤗
datasets:
  - paulkm/autotrain-data-lottery_prod_v3
co2_eq_emissions:
  emissions: 3.67386840637788

Model Trained Using AutoTrain

• Problem type: Binary Classification
• Model ID: 3409393337
• CO2 Emissions (in grams): 3.6739

Validation Metrics

• Loss: 0.244
• Accuracy: 0.909
• Precision: 0.922
• Recall: 0.875
• AUC: 0.953
• F1: 0.898

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/paulkm/autotrain-lottery_prod_v3-3409393337

Or Python API:

from transformers import AutoModelForSequenceClassification, AutoTokenizer

model = AutoModelForSequenceClassification.from_pretrained("paulkm/autotrain-lottery_prod_v3-3409393337", use_auth_token=True)

tokenizer = AutoTokenizer.from_pretrained("paulkm/autotrain-lottery_prod_v3-3409393337", use_auth_token=True)

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

outputs = model(**inputs)