--- tags: autonlp language: unk widget: - text: "I love AutoNLP 🤗" datasets: - rodrigogelacio/autonlp-data-department-classification co2_eq_emissions: 1.4862856774320061 --- # Model Trained Using AutoNLP - Problem type: Multi-class Classification - Model ID: 534915130 - CO2 Emissions (in grams): 1.4862856774320061 ## Validation Metrics - Loss: 0.37066277861595154 - Accuracy: 0.9204545454545454 - Macro F1: 0.9103715740678612 - Micro F1: 0.9204545454545455 - Weighted F1: 0.9196871607509906 - Macro Precision: 0.9207759152612094 - Micro Precision: 0.9204545454545454 - Weighted Precision: 0.922177301864802 - Macro Recall: 0.9055002187355129 - Micro Recall: 0.9204545454545454 - Weighted Recall: 0.9204545454545454 ## 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 AutoNLP"}' https://api-inference.huggingface.co/models/rodrigogelacio/autonlp-department-classification-534915130 ``` Or Python API: ``` from transformers import AutoModelForSequenceClassification, AutoTokenizer model = AutoModelForSequenceClassification.from_pretrained("rodrigogelacio/autonlp-department-classification-534915130", use_auth_token=True) tokenizer = AutoTokenizer.from_pretrained("rodrigogelacio/autonlp-department-classification-534915130", use_auth_token=True) inputs = tokenizer("I love AutoNLP", return_tensors="pt") outputs = model(**inputs) ```