README.md

metadata

tags: autotrain
language: unk
widget:
  - text: I love AutoTrain 🤗
datasets:
  - vlsb/autotrain-data-security-texts-classification-distilroberta
co2_eq_emissions: 2.0817207656772445

Model Trained Using AutoTrain

• Problem type: Binary Classification
• Model ID: 688220764
• CO2 Emissions (in grams): 2.0817207656772445

Validation Metrics

• Loss: 0.3055502772331238
• Accuracy: 0.9030612244897959
• Precision: 0.9528301886792453
• Recall: 0.8782608695652174
• AUC: 0.9439076757917337
• F1: 0.9140271493212669

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/vlsb/autotrain-security-texts-classification-distilroberta-688220764

Or Python API:

from transformers import AutoModelForSequenceClassification, AutoTokenizer

model = AutoModelForSequenceClassification.from_pretrained("vlsb/autotrain-security-texts-classification-distilroberta-688220764", use_auth_token=True)

tokenizer = AutoTokenizer.from_pretrained("vlsb/autotrain-security-texts-classification-distilroberta-688220764", use_auth_token=True)

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

outputs = model(**inputs)