Text Classification
Transformers
PyTorch
ONNX
Safetensors
English
deberta
Trained with AutoTrain
Inference Endpoints
Text-Moderation / README.md
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metadata
tags:
  - autotrain
  - text-classification
language:
  - en
widget:
  - text: I love AutoTrain
datasets:
  - DarwinAnim8or/autotrain-data-text-moderation-v2-small
co2_eq_emissions:
  emissions: 0.03967468113268738

Model Trained Using AutoTrain

  • Problem type: Multi-class Classification
  • Model ID: 93240145801
  • CO2 Emissions (in grams): 0.0397

Validation Metrics

  • Loss: 0.848
  • Accuracy: 0.749
  • Macro F1: 0.326
  • Micro F1: 0.749
  • Weighted F1: 0.703
  • Macro Precision: 0.321
  • Micro Precision: 0.749
  • Weighted Precision: 0.671
  • Macro Recall: 0.349
  • Micro Recall: 0.749
  • Weighted Recall: 0.749

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/DarwinAnim8or/autotrain-text-moderation-v2-small-93240145801

Or Python API:

from transformers import AutoModelForSequenceClassification, AutoTokenizer

model = AutoModelForSequenceClassification.from_pretrained("DarwinAnim8or/autotrain-text-moderation-v2-small-93240145801", use_auth_token=True)

tokenizer = AutoTokenizer.from_pretrained("DarwinAnim8or/autotrain-text-moderation-v2-small-93240145801", use_auth_token=True)

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

outputs = model(**inputs)