--- tags: - autotrain - text-classification language: - ko widget: - text: "익일 화물 알려줘" datasets: - yeye776/autotrain-data-intent-classification-6categories-auto co2_eq_emissions: emissions: 0.45662908042466266 --- # Model Trained Using AutoTrain - Problem type: Multi-class Classification - Model ID: 88901143797 - CO2 Emissions (in grams): 0.4566 ## Validation Metrics - Loss: 0.042 - Accuracy: 1.000 - Macro F1: 1.000 - Micro F1: 1.000 - Weighted F1: 1.000 - Macro Precision: 1.000 - Micro Precision: 1.000 - Weighted Precision: 1.000 - Macro Recall: 1.000 - Micro Recall: 1.000 - Weighted Recall: 1.000 ## Dataset Label | Label | intent(category) | | ------------ | ------------------- | | 11 | 날씨 | | 12 | 장소안내 | | 13 | 전화연결 | | 14 | 일상대화 | | 15 | 화물추천 | | 16 |검색(FAQ)| ## 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/yeye776/autotrain-intent-classification-6categories-auto-88901143797 ``` Or Python API: ``` from transformers import AutoModelForSequenceClassification, AutoTokenizer model = AutoModelForSequenceClassification.from_pretrained("yeye776/autotrain-intent-classification-6categories-auto-88901143797", use_auth_token=True) tokenizer = AutoTokenizer.from_pretrained("yeye776/autotrain-intent-classification-6categories-auto-88901143797", use_auth_token=True) inputs = tokenizer("익일 화물 알려줘", return_tensors="pt") outputs = model(**inputs) ```