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bitmorse
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autonlp-ks-530615016

Text Classification
Transformers
PyTorch
English
distilbert
Trained with AutoTrain
Carbon Emissions
Inference Endpoints
Model card Files Community
autonlp-ks-530615016 / README.md
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metadata
tags: autonlp
language: en
widget:
  - text: I love AutoNLP 🤗
datasets:
  - bitmorse/autonlp-data-ks
co2_eq_emissions: 2.2247356264808964

Model Trained Using AutoNLP

  • Problem type: Multi-class Classification
  • Model ID: 530615016
  • CO2 Emissions (in grams): 2.2247356264808964

Validation Metrics

  • Loss: 0.7859578132629395
  • Accuracy: 0.676854818831649
  • Macro F1: 0.3297126297995653
  • Micro F1: 0.676854818831649
  • Weighted F1: 0.6429522696884535
  • Macro Precision: 0.33152557743856437
  • Micro Precision: 0.676854818831649
  • Weighted Precision: 0.6276125515413322
  • Macro Recall: 0.33784302289888885
  • Micro Recall: 0.676854818831649
  • Weighted Recall: 0.676854818831649

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/bitmorse/autonlp-ks-530615016

Or Python API:

from transformers import AutoModelForSequenceClassification, AutoTokenizer

model = AutoModelForSequenceClassification.from_pretrained("bitmorse/autonlp-ks-530615016", use_auth_token=True)

tokenizer = AutoTokenizer.from_pretrained("bitmorse/autonlp-ks-530615016", use_auth_token=True)

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

outputs = model(**inputs)