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metadata
tags:
  - autotrain
  - text-classification
language:
  - it
widget:
  - text: I love AutoTrain 🤗
datasets:
  - davanstrien/autotrain-data-cultural_heritage_metadata_accuracy
co2_eq_emissions:
  emissions: 7.171395981202868

Model Trained Using AutoTrain

  • Problem type: Multi-class Classification
  • Model ID: 48840118272
  • CO2 Emissions (in grams): 7.1714

Validation Metrics

  • Loss: 0.085
  • Accuracy: 0.972
  • Macro F1: 0.972
  • Micro F1: 0.972
  • Weighted F1: 0.972
  • Macro Precision: 0.972
  • Micro Precision: 0.972
  • Weighted Precision: 0.972
  • Macro Recall: 0.972
  • Micro Recall: 0.972
  • Weighted Recall: 0.972

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"}' /static-proxy?url=https%3A%2F%2Fapi-inference.huggingface.co%2Fmodels%2Fdavanstrien%2Fautotrain-cultural_heritage_metadata_accuracy-48840118272

Or Python API:

from transformers import AutoModelForSequenceClassification, AutoTokenizer

model = AutoModelForSequenceClassification.from_pretrained("davanstrien/autotrain-cultural_heritage_metadata_accuracy-48840118272", use_auth_token=True)

tokenizer = AutoTokenizer.from_pretrained("davanstrien/autotrain-cultural_heritage_metadata_accuracy-48840118272", use_auth_token=True)

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

outputs = model(**inputs)