| --- |
| 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) |
| ``` |
