--- tags: autotrain language: ar widget: - text: "I love AutoTrain 🤗" datasets: - Yah216/autotrain-data-Poem_Rawiy_detection co2_eq_emissions: 1.8046766441629636 --- # Model Trained Using AutoTrain - Problem type: Multi-class Classification - Model ID: 918730150 - CO2 Emissions (in grams): 1.8046766441629636 ## Validation Metrics - Loss: 0.398613303899765 - Accuracy: 0.912351981006084 - Macro F1: 0.717311758991278 - Micro F1: 0.912351981006084 - Weighted F1: 0.9110094798809955 - Macro Precision: 0.7211917136609866 - Micro Precision: 0.912351981006084 - Weighted Precision: 0.9102294701380585 - Macro Recall: 0.714852045042265 - Micro Recall: 0.912351981006084 - Weighted Recall: 0.912351981006084 ## 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/Yah216/autotrain-Poem_Rawiy_detection-918730150 ``` Or Python API: ``` from transformers import AutoModelForSequenceClassification, AutoTokenizer model = AutoModelForSequenceClassification.from_pretrained("Yah216/autotrain-Poem_Rawiy_detection-918730150", use_auth_token=True) tokenizer = AutoTokenizer.from_pretrained("Yah216/autotrain-Poem_Rawiy_detection-918730150", use_auth_token=True) inputs = tokenizer("I love AutoTrain", return_tensors="pt") outputs = model(**inputs) ```