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staceythompson
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autonlp-new-text-classification-38319698

Text Classification
Transformers
PyTorch
Enawené-Nawé
distilbert
Trained with AutoTrain
Inference Endpoints
Model card Files Community
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autonlp-new-text-classification-38319698 / README.md
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metadata
tags: autonlp
language: unk
widget:
  - text: I love AutoNLP 🤗
datasets:
  - staceythompson/autonlp-data-new-text-classification
co2_eq_emissions: 2.0318857468309206

Model Trained Using AutoNLP

  • Problem type: Multi-class Classification
  • Model ID: 38319698
  • CO2 Emissions (in grams): 2.0318857468309206

Validation Metrics

  • Loss: 0.04461582377552986
  • Accuracy: 0.9909255898366606
  • Macro F1: 0.9951842095089771
  • Micro F1: 0.9909255898366606
  • Weighted F1: 0.9909493945587176
  • Macro Precision: 0.9942196531791907
  • Micro Precision: 0.9909255898366606
  • Weighted Precision: 0.9911878560263526
  • Macro Recall: 0.9962686567164181
  • Micro Recall: 0.9909255898366606
  • Weighted Recall: 0.9909255898366606

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 AutoNLP"}' https://api-inference.huggingface.co/models/staceythompson/autonlp-new-text-classification-38319698

Or Python API:

from transformers import AutoModelForSequenceClassification, AutoTokenizer

model = AutoModelForSequenceClassification.from_pretrained("staceythompson/autonlp-new-text-classification-38319698", use_auth_token=True)

tokenizer = AutoTokenizer.from_pretrained("staceythompson/autonlp-new-text-classification-38319698", use_auth_token=True)

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

outputs = model(**inputs)