--- tags: autotrain language: unk widget: - text: "I love AutoTrain 🤗" datasets: - Amalq/autotrain-data-smm4h_large_roberta_clean co2_eq_emissions: 9.123490454955585 --- # Model Trained Using AutoTrain - Problem type: Binary Classification - Model ID: 874027878 - CO2 Emissions (in grams): 9.123490454955585 ## Validation Metrics - Loss: 0.35724225640296936 - Accuracy: 0.8571428571428571 - Precision: 0.7637362637362637 - Recall: 0.8910256410256411 - AUC: 0.9267555361305361 - F1: 0.8224852071005917 ## 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/Amalq/autotrain-smm4h_large_roberta_clean-874027878 ``` Or Python API: ``` from transformers import AutoModelForSequenceClassification, AutoTokenizer model = AutoModelForSequenceClassification.from_pretrained("Amalq/autotrain-smm4h_large_roberta_clean-874027878", use_auth_token=True) tokenizer = AutoTokenizer.from_pretrained("Amalq/autotrain-smm4h_large_roberta_clean-874027878", use_auth_token=True) inputs = tokenizer("I love AutoTrain", return_tensors="pt") outputs = model(**inputs) ```