paulkm
/

chinese_spam_detect

Text Classification

Trained with AutoTrain

Carbon Emissions

Inference Endpoints

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Model Trained Using AutoTrain

Problem type: Binary Classification
Model ID: 2415675346
CO2 Emissions (in grams): 0.8148

Validation Metrics

Loss: 0.041
Accuracy: 0.992
Precision: 0.993
Recall: 0.990
AUC: 0.999
F1: 0.991

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/paulkm/autotrain-spam_full-2415675346

Or Python API:

from transformers import AutoModelForSequenceClassification, AutoTokenizer

model = AutoModelForSequenceClassification.from_pretrained("paulkm/autotrain-spam_full-2415675346", use_auth_token=True)

tokenizer = AutoTokenizer.from_pretrained("paulkm/autotrain-spam_full-2415675346", use_auth_token=True)

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

outputs = model(**inputs)

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Text Classification

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