Text Classification
PEFT
Safetensors
English
entity-matching
person-name-matching
record-linkage
deduplication
lora
deberta-v3
Instructions to use LessLM/person-name-match-likelihood-v6 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use LessLM/person-name-match-likelihood-v6 with PEFT:
from peft import PeftModel from transformers import AutoModelForSequenceClassification base_model = AutoModelForSequenceClassification.from_pretrained("MoritzLaurer/DeBERTa-v3-base-mnli-fever-anli") model = PeftModel.from_pretrained(base_model, "LessLM/person-name-match-likelihood-v6") - Notebooks
- Google Colab
- Kaggle
File size: 671 Bytes
16dad5b | 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 | {
"add_prefix_space": true,
"backend": "tokenizers",
"bos_token": "[CLS]",
"clean_up_tokenization_spaces": true,
"cls_token": "[CLS]",
"do_lower_case": false,
"eos_token": "[SEP]",
"extra_special_tokens": [
"[FIRST]",
"[LAST]",
"[TITLE]",
"[SUFFIX]",
"[NICK]",
"[MIDDLE]",
"[LEGAL]",
"[ABBREV]",
"[TRADE]"
],
"is_local": false,
"mask_token": "[MASK]",
"model_max_length": 1000000000000000019884624838656,
"pad_token": "[PAD]",
"sep_token": "[SEP]",
"sp_model_kwargs": {},
"split_by_punct": false,
"tokenizer_class": "DebertaV2Tokenizer",
"unk_id": 3,
"unk_token": "[UNK]",
"vocab_type": "spm"
}
|