Text Classification
Transformers
ONNX
Safetensors
German
xlm-roberta
job-classification
german
sales-classification
taxonomy-sales
text-embeddings-inference
Instructions to use Ashybalka/xlm-roberta-taxonomy-sales-de with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Ashybalka/xlm-roberta-taxonomy-sales-de with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Ashybalka/xlm-roberta-taxonomy-sales-de")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Ashybalka/xlm-roberta-taxonomy-sales-de") model = AutoModelForSequenceClassification.from_pretrained("Ashybalka/xlm-roberta-taxonomy-sales-de", device_map="auto") - Notebooks
- Google Colab
- Kaggle
| precision recall f1-score support | |
| Business Development & Strategic Sales 0.852 0.868 0.860 53 | |
| Field Sales & Outside Sales 0.925 0.876 0.900 226 | |
| Inside Sales & Telesales 0.951 0.879 0.913 132 | |
| Key Account & Account Management 0.879 0.892 0.885 65 | |
| Retail & Store Sales 0.982 0.982 0.982 500 | |
| Sales Management & Leadership 0.760 0.864 0.809 44 | |
| Sales Operations & Support 0.759 0.936 0.838 47 | |
| Technical Sales & Sales Engineering 0.824 0.875 0.848 48 | |
| accuracy 0.926 1115 | |
| macro avg 0.866 0.896 0.879 1115 | |
| weighted avg 0.930 0.926 0.927 1115 | |