Instructions to use VinayNR/stats-nerd with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Flair
How to use VinayNR/stats-nerd with Flair:
from flair.models import SequenceTagger tagger = SequenceTagger.load("VinayNR/stats-nerd") - Notebooks
- Google Colab
- Kaggle
| from flair.data import Tokenizer | |
| from typing import List | |
| class StatsTokenizer(Tokenizer): | |
| def __init__(self): | |
| super(StatsTokenizer, self).__init__() | |
| def tokenize(self, text: str) -> List[str]: | |
| return StatsTokenizer.run_tokenize(text) | |
| def run_tokenize(text: str) -> List[str]: | |
| tokens: List[str] = [] | |
| index = -1 | |
| words = text.split() | |
| for word in words: | |
| token = "" | |
| for index, char in enumerate(word): | |
| if char in [',']: | |
| if len(token) > 0: | |
| tokens.append(token) | |
| token = "" | |
| elif char in ['(', ')', '<', '=']: | |
| if len(token) > 0: | |
| tokens.append(token) | |
| tokens.append(char) | |
| token = "" | |
| else: | |
| token += char | |
| if len(token) > 0: | |
| if token.endswith('.'): | |
| token = token[:-1] | |
| tokens.append(token) | |
| return tokens |