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HonOR, standing for "Hyper-parameter tuned computer-generated text objectification utilizing BERTForSeqenceClassification" is a binary text classification model built with BertForSequenceClassification. This model was built to explore possibilities for zero-shot classification of texts in a wide range of domains.

For more information, please see the model card.

Model information

  • Problem type: Binary Classification
  • Model ID: 2514377451
  • CO2 Emissions (in grams): 14.4613

Validation metrics

  • Loss: 0.055
  • Accuracy: 0.989
  • Precision: 0.995
  • Recall: 0.983
  • AUC: 0.998
  • F1: 0.989

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/freddiezhang/autotrain-honor-2514377451

Or a Python API:

from transformers import AutoModelForSequenceClassification, AutoTokenizer

model = AutoModelForSequenceClassification.from_pretrained("freddiezhang/autotrain-honor-2514377451", use_auth_token=True)

tokenizer = AutoTokenizer.from_pretrained("freddiezhang/autotrain-honor-2514377451", use_auth_token=True)

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

outputs = model(**inputs)
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Dataset used to train freddiezhang/honor

Space using freddiezhang/honor 1