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
| { | |
| "architectures": [ | |
| "XLMRobertaForSequenceClassification" | |
| ], | |
| "attention_probs_dropout_prob": 0.1, | |
| "bos_token_id": 0, | |
| "classifier_dropout": null, | |
| "dtype": "float32", | |
| "eos_token_id": 2, | |
| "hidden_act": "gelu", | |
| "hidden_dropout_prob": 0.1, | |
| "hidden_size": 768, | |
| "id2label": { | |
| "0": "Business Development & Strategic Sales", | |
| "1": "Field Sales & Outside Sales", | |
| "2": "Inside Sales & Telesales", | |
| "3": "Key Account & Account Management", | |
| "4": "Retail & Store Sales", | |
| "5": "Sales Management & Leadership", | |
| "6": "Sales Operations & Support", | |
| "7": "Technical Sales & Sales Engineering" | |
| }, | |
| "initializer_range": 0.02, | |
| "intermediate_size": 3072, | |
| "label2id": { | |
| "Business Development & Strategic Sales": 0, | |
| "Field Sales & Outside Sales": 1, | |
| "Inside Sales & Telesales": 2, | |
| "Key Account & Account Management": 3, | |
| "Retail & Store Sales": 4, | |
| "Sales Management & Leadership": 5, | |
| "Sales Operations & Support": 6, | |
| "Technical Sales & Sales Engineering": 7 | |
| }, | |
| "layer_norm_eps": 1e-05, | |
| "max_position_embeddings": 514, | |
| "model_type": "xlm-roberta", | |
| "num_attention_heads": 12, | |
| "num_hidden_layers": 12, | |
| "output_past": true, | |
| "pad_token_id": 1, | |
| "position_embedding_type": "absolute", | |
| "transformers_version": "4.57.6", | |
| "type_vocab_size": 1, | |
| "use_cache": true, | |
| "vocab_size": 250002 | |
| } | |