--- tags: - autotrain - text-classification language: - unk widget: - text: "I love AutoTrain 🤗" datasets: - Plenng/autotrain-data-mt5-sentiment-test co2_eq_emissions: emissions: 0.0015570156369928603 --- # Model Trained Using AutoTrain - Problem type: Binary Classification - Model ID: 50714120989 - CO2 Emissions (in grams): 0.0016 ## Validation Metrics - Loss: 0.469 - Accuracy: 0.818 - Precision: 0.769 - Recall: 0.909 - AUC: 0.917 - F1: 0.833 ## 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/Plenng/autotrain-mt5-sentiment-test-50714120989 ``` Or Python API: ``` from transformers import AutoModelForSequenceClassification, AutoTokenizer model = AutoModelForSequenceClassification.from_pretrained("Plenng/autotrain-mt5-sentiment-test-50714120989", use_auth_token=True) tokenizer = AutoTokenizer.from_pretrained("Plenng/autotrain-mt5-sentiment-test-50714120989", use_auth_token=True) inputs = tokenizer("I love AutoTrain", return_tensors="pt") outputs = model(**inputs) ```