README.md

metadata

tags:
  - autotrain
  - text-classification
language:
  - de
widget:
  - text: I love AutoTrain 🤗
datasets:
  - BIDEQUITY/autotrain-data-bidequity-page-classifier
co2_eq_emissions:
  emissions: 1.316894718008702

Model Trained Using AutoTrain

• Problem type: Multi-class Classification
• Model ID: 49442119390
• CO2 Emissions (in grams): 1.3169

Validation Metrics

• Loss: 0.416
• Accuracy: 0.870
• Macro F1: 0.781
• Micro F1: 0.870
• Weighted F1: 0.864
• Macro Precision: 0.888
• Micro Precision: 0.870
• Weighted Precision: 0.878
• Macro Recall: 0.752
• Micro Recall: 0.870
• Weighted Recall: 0.870

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/BIDEQUITY/autotrain-bidequity-page-classifier-49442119390

Or Python API:

from transformers import AutoModelForSequenceClassification, AutoTokenizer

model = AutoModelForSequenceClassification.from_pretrained("BIDEQUITY/autotrain-bidequity-page-classifier-49442119390", use_auth_token=True)

tokenizer = AutoTokenizer.from_pretrained("BIDEQUITY/autotrain-bidequity-page-classifier-49442119390", use_auth_token=True)

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

outputs = model(**inputs)