| from typing import List | |
| import os | |
| import fasttext.util | |
| class PreTrainedPipeline(): | |
| def __init__(self, path=""): | |
| """ | |
| Initialize model | |
| """ | |
| self.model = fasttext.load_model(os.path.join(path, 'debate2vec.bin')) | |
| def __call__(self, inputs: str) -> List[List[Dict[str, float]]]: | |
| """ | |
| Args: | |
| inputs (:obj:`str`): | |
| a string containing some text | |
| Return: | |
| A :obj:`list`:. The object returned should be a list of one list like [[{"label": 0.9939950108528137}]] containing : | |
| - "label": A string representing what the label/class is. There can be multiple labels. | |
| - "score": A score between 0 and 1 describing how confident the model is for this label/class. | |
| """ | |
| preds = self.model.get_nearest_neighbors("dog", k=10) | |
| result = [] | |
| for distance, word in preds: | |
| result.append({"label": word, "score": distance}) | |
| return [result] | |