Token Classification
Transformers
Safetensors
Arabic
bert
hadith
sanad
matn
hadith-separator
hadith_separator
islam
hadithBERT
Instructions to use SHK4K/hadith-segmentation-bert with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use SHK4K/hadith-segmentation-bert with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="SHK4K/hadith-segmentation-bert")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("SHK4K/hadith-segmentation-bert") model = AutoModelForTokenClassification.from_pretrained("SHK4K/hadith-segmentation-bert") - Notebooks
- Google Colab
- Kaggle
File size: 480 Bytes
2fca02e | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 | {
"backend": "tokenizers",
"cls_token": "[CLS]",
"do_basic_tokenize": true,
"do_lower_case": false,
"is_local": false,
"local_files_only": false,
"mask_token": "[MASK]",
"max_len": 512,
"model_max_length": 512,
"never_split": [
"[بريد]",
"[مستخدم]",
"[رابط]"
],
"pad_token": "[PAD]",
"sep_token": "[SEP]",
"strip_accents": null,
"tokenize_chinese_chars": true,
"tokenizer_class": "BertTokenizer",
"unk_token": "[UNK]"
}
|