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--- |
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tags: autotrain |
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language: unk |
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widget: |
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- text: "I love AutoTrain 🤗" |
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datasets: |
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- vlsb/autotrain-data-security-texts-classification-distilroberta |
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co2_eq_emissions: 2.0817207656772445 |
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--- |
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# Model Trained Using AutoTrain |
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- Problem type: Binary Classification |
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- Model ID: 688220764 |
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- CO2 Emissions (in grams): 2.0817207656772445 |
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## Validation Metrics |
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- Loss: 0.3055502772331238 |
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- Accuracy: 0.9030612244897959 |
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- Precision: 0.9528301886792453 |
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- Recall: 0.8782608695652174 |
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- AUC: 0.9439076757917337 |
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- F1: 0.9140271493212669 |
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## Usage |
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You can use cURL to access this model: |
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``` |
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$ 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 |
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``` |
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Or Python API: |
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``` |
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from transformers import AutoModelForSequenceClassification, AutoTokenizer |
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model = AutoModelForSequenceClassification.from_pretrained("vlsb/autotrain-security-texts-classification-distilroberta-688220764", use_auth_token=True) |
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tokenizer = AutoTokenizer.from_pretrained("vlsb/autotrain-security-texts-classification-distilroberta-688220764", use_auth_token=True) |
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inputs = tokenizer("I love AutoTrain", return_tensors="pt") |
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outputs = model(**inputs) |
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``` |
