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
File size: 1,370 Bytes
3c0613a | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 | {
"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
}
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