--- tags: autonlp language: unk widget: - text: "I love AutoNLP 🤗" datasets: - Jeska/autonlp-data-vaccinfaq co2_eq_emissions: 27.135492487925884 --- # Model Trained Using AutoNLP - Problem type: Multi-class Classification - Model ID: 22144706 - CO2 Emissions (in grams): 27.135492487925884 ## Validation Metrics - Loss: 1.81697416305542 - Accuracy: 0.6377269139700079 - Macro F1: 0.5181293370145044 - Micro F1: 0.6377269139700079 - Weighted F1: 0.631117826235572 - Macro Precision: 0.5371452512845428 - Micro Precision: 0.6377269139700079 - Weighted Precision: 0.6655055695465463 - Macro Recall: 0.5609328178925124 - Micro Recall: 0.6377269139700079 - Weighted Recall: 0.6377269139700079 ## 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/Jeska/autonlp-vaccinfaq-22144706 ``` Or Python API: ``` from transformers import AutoModelForSequenceClassification, AutoTokenizer model = AutoModelForSequenceClassification.from_pretrained("Jeska/autonlp-vaccinfaq-22144706", use_auth_token=True) tokenizer = AutoTokenizer.from_pretrained("Jeska/autonlp-vaccinfaq-22144706", use_auth_token=True) inputs = tokenizer("I love AutoNLP", return_tensors="pt") outputs = model(**inputs) ```