README.md

metadata

tags:
  - autotrain
  - text-classification
language:
  - unk
widget:
  - text: I love AutoTrain 🤗
datasets:
  - Saripudin/autotrain-data-bbc-news-classifier
co2_eq_emissions:
  emissions: 0.005887858067537627

Model Trained Using AutoTrain

• Problem type: Multi-class Classification
• Model ID: 3523995259
• CO2 Emissions (in grams): 0.0059

Validation Metrics

• Loss: 0.422
• Accuracy: 1.000
• Macro F1: 1.000
• Micro F1: 1.000
• Weighted F1: 1.000
• Macro Precision: 1.000
• Micro Precision: 1.000
• Weighted Precision: 1.000
• Macro Recall: 1.000
• Micro Recall: 1.000
• Weighted Recall: 1.000

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/Saripudin/autotrain-bbc-news-classifier-3523995259

Or Python API:

from transformers import AutoModelForSequenceClassification, AutoTokenizer

model = AutoModelForSequenceClassification.from_pretrained("Saripudin/autotrain-bbc-news-classifier-3523995259", use_auth_token=True)

tokenizer = AutoTokenizer.from_pretrained("Saripudin/autotrain-bbc-news-classifier-3523995259", use_auth_token=True)

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

outputs = model(**inputs)