--- tags: autonlp language: unk widget: - text: "I love AutoNLP 🤗" datasets: - dee4hf/autonlp-data-shajBERT co2_eq_emissions: 11.98841452241473 --- # Model Trained Using AutoNLP - Problem type: Multi-class Classification - Model ID: 38639804 - CO2 Emissions (in grams): 11.98841452241473 ## Validation Metrics - Loss: 0.421400249004364 - Accuracy: 0.86783988957902 - Macro F1: 0.8669477050676501 - Micro F1: 0.86783988957902 - Weighted F1: 0.86694770506765 - Macro Precision: 0.867606300132228 - Micro Precision: 0.86783988957902 - Weighted Precision: 0.8676063001322278 - Macro Recall: 0.86783988957902 - Micro Recall: 0.86783988957902 - Weighted Recall: 0.86783988957902 ## 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/dee4hf/autonlp-shajBERT-38639804 ``` Or Python API: ``` from transformers import AutoModelForSequenceClassification, AutoTokenizer model = AutoModelForSequenceClassification.from_pretrained("dee4hf/autonlp-shajBERT-38639804", use_auth_token=True) tokenizer = AutoTokenizer.from_pretrained("dee4hf/autonlp-shajBERT-38639804", use_auth_token=True) inputs = tokenizer("I love AutoNLP", return_tensors="pt") outputs = model(**inputs) ```