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fix: Multiple Getter Calls in class-transformertype: fixIssues describing a broken feature. #1707 openedMay 31, 2024byJHyeok 1 fix: incorrect property name in validation messages when using @Expose()status: needs triageIssues which needs to be reproduced to be verified report.type: fixIssues des...
classification import ClassificationModel import pandas as pd # Train and Evaluation data needs to be in a Pandas Dataframe of two columns. The first column is the text with type str, and the second column is the label with type int. train_data = [['Example sentence belonging to class 1'...
Overall, these findings suggest that using recurrent layer recurrent class neural networks combined with some kind of attentional mechanism achieves better prediction accuracy in hydrologic forecasting tasks (Alizadeh et al., 2021; Ding et al., 2020; Wei et al., 2023). However, with time-step ...
8 Class-transformer allows you to transform plain object to some instance of class and versa. 9 Also it allows to serialize / deserialize object based on criteria. 10 This tool is super useful on both frontend and backend. 11 12 Example how to use with angular 2 in [plunker](http...
In this article, a quasi-switched boost converter based on the switched-capacitor technique with high step-up voltage capability is dealt with and analyzed. The proposed converter offers a simple structure and low voltage stress on the semiconductor elem
Basic current measurement was performed using a class 0.1 current transformer together with an event recorder. The basic measurement was supplemented by the recording of the current derivative using a Rogowski coil [35]. Due to the dependence of the transformer inrush current on the initial phase ...
classClassNameTransformer:ValueTransformer{overrideclassfunctransformedValueClass() ->AnyClass{returnNSString.self}overrideclassfuncallowsReverseTransformation() ->Bool{returnfalse}overridefunctransformedValue(_value:Any?) ->Any?{return(valueasAnyObject).className}}extensionNSValueTransformerName{staticletclassNam...
In [2] class Compose: """ Do transformation on input data with corresponding pre-processing and augmentation operations. The shape of input data to all operations is [height, width, channels]. Args: transforms (list): A list contains data pre-processing or augmentation. Empty list means only...
classLLM methodLLM.__init__ __init__(model_path:str,model_type:str,config:Optional[ctransformers.llm.Config]=None,lib:Optional[str]=None) Loads the language model from a local file. Args: model_path: The path to a model file.