Token Classification
Transformers
PyTorch
Safetensors
German
xlm-roberta
legal
tax law
relation extraction
entity extraction
Instructions to use danielsteinigen/KeyFiTax with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use danielsteinigen/KeyFiTax with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="danielsteinigen/KeyFiTax")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("danielsteinigen/KeyFiTax") model = AutoModelForTokenClassification.from_pretrained("danielsteinigen/KeyFiTax", device_map="auto") - Notebooks
- Google Colab
- Kaggle
File size: 522 Bytes
ac775f9 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 | {
"bos_token": "<s>",
"cls_token": "<s>",
"eos_token": "</s>",
"mask_token": {
"__type": "AddedToken",
"content": "<mask>",
"lstrip": true,
"normalized": true,
"rstrip": false,
"single_word": false
},
"max_length": 512,
"model_max_length": 512,
"name_or_path": "xlm-roberta-large",
"pad_token": "<pad>",
"padding": "max_length",
"sep_token": "</s>",
"special_tokens_map_file": null,
"tokenizer_class": "XLMRobertaTokenizer",
"truncation": true,
"unk_token": "<unk>"
}
|