Search Results for "batch text replace"

DeepDoctection is a document AI framework that applies deep learning techniques to analyze and extract structured data from scanned documents, PDFs, and images. deepdoctection is a Python library that orchestrates document extraction and document layout analysis tasks using deep learning models. It does not implement models but enables you to build pipelines using highly acknowledged libraries for object detection, OCR and selected NLP tasks and provides an integrated frameworks for...

Eng2BN CSV Translator user-friendly Python tool that enables efficient translation of English text to Bangla within CSV files. The application supports large datasets and allows users to translate specific row ranges, making it ideal for batch processing.

...Given one or more source documents and a set of keywords, it extracts all nouns, compares them semantically to the keywords using a pretrained NLP model, and produces a structured, hierarchical index ready to be included in a book or manuscript. LexiFinder works in two ways: as a command-line tool for scripting, automation, and batch processing, and as a graphical application for a guided, point-and-click experience. Both interfaces share the same underlying engine and support the same features. Supported input formats are PDF, DOCX, and ODT. The index can be exported as plain text, JSON, CSV, or HTML.

Transformers4Rec is an advanced recommendation system library that leverages Transformer models for sequential and session-based recommendations. The library works as a bridge between natural language processing (NLP) and recommender systems (RecSys) by integrating with one of the most popular NLP frameworks, Hugging Face Transformers (HF). Transformers4Rec makes state-of-the-art transformer architectures available for RecSys researchers and industry practitioners. Traditional recommendation...

...It’s built with the very latest research in mind, and was designed from day one to support rapid prototyping. PyTorch-NLP comes with pre-trained embeddings, samplers, dataset loaders, metrics, neural network modules and text encoders. It’s open-source software, released under the BSD3 license. With your batch in hand, you can use PyTorch to develop and train your model using gradient descent. For example, check out this example code for training on the Stanford Natural Language Inference (SNLI) Corpus. Now you've setup your pipeline, you may want to ensure that some functions run deterministically. ...