Search Results for "translation-pack" - Page 4
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Showing 197 open source projects for "translation-pack"
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Sockeye
Sequence-to-sequence framework, focused on Neural Machine Translation
Sockeye is an open-source sequence-to-sequence framework for Neural Machine Translation built on PyTorch. It implements distributed training and optimized inference for state-of-the-art models, powering Amazon Translate and other MT applications. For a quickstart guide to training a standard NMT model on any size of data, see the WMT 2014 English-German tutorial. If you are interested in collaborating or have any questions, please submit a pull request or issue. -
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Tkinter Designer
An easy and fast way to create a Python GUI
Tkinter-Designer is a tool that allows developers to generate Python GUI code using Tkinter directly from Figma designs. By leveraging Figma’s design export capabilities, the tool parses the layout and transforms it into a working Tkinter interface. This helps streamline UI development by bridging the gap between design and code, making it accessible for developers and designers alike. -
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Screen Translate
An OCR translator tool made by utilizing tesseract & python-opencv
...For full view of the project you can check the Github repository: https://github.com/Dadangdut33/Screen-Translate REQUIREMENTS - Tesseract : https://github.com/UB-Mannheim/tesseract/wiki. Needed for the ocr. Install it with all the language pack. - Libretranslate (Optional for offline translation support) - Internet connection for translation if not using libretranslate # Tutorial on How To Setup https://github.com/Dadangdut33/Screen-Translate#installation-and-setup -
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TextBox
A text generation library with pre-trained language models github.com
TextBox 2.0 is an up-to-date text generation library based on Python and PyTorch focusing on building a unified and standardized pipeline for applying pre-trained language models to text generation. From a task perspective, we consider 13 common text generation tasks such as translation, story generation, and style transfer, and their corresponding 83 widely-used datasets. From a model perspective, we incorporate 47 pre-trained language models/modules covering the categories of general, translation, Chinese, dialogue, controllable, distilled, prompting, and lightweight models (modules). From a training perspective, we support 4 pre-training objectives and 4 efficient and robust training strategies, such as distributed data parallel and efficient generation. ... -
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d2l-zh
Chinese-language edition of Dive into Deep Learning
d2l‑zh is the Chinese-language edition of Dive into Deep Learning, an interactive, open‑source deep learning textbook that combines code, math, and explanatory text. It features runnable Jupyter notebooks compatible with multiple frameworks (e.g., PyTorch, MXNet, TensorFlow), comprehensive theoretical analysis, and exercises. Widely adopted in over 70 countries and used by more than 500 universities for teaching deep learning. -
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Alphafold2
Unofficial Pytorch implementation / replication of Alphafold2
...Once this is replicated, I intend to fold all available amino acid sequences out there in-silico and release it as an academic torrent, to further science. Deepmind has open sourced the official code in Jax, along with the weights! This repository will now be geared towards a straight pytorch translation with some improvements on positional encoding. lhatsk has reported training a modified trunk of this repository, using the same setup as trRosetta, with competitive results. The underlying assumption is that the trunk works on the residue level, and then constitutes to atomic level for the structure module, whether it be SE3 Transformers, E(n)-Transformer, or EGNN doing the refinement. -
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Fairseq
Facebook AI Research Sequence-to-Sequence Toolkit written in Python
Fairseq(-py) is a sequence modeling toolkit that allows researchers and developers to train custom models for translation, summarization, language modeling and other text generation tasks. We provide reference implementations of various sequence modeling papers. Recent work by Microsoft and Google has shown that data parallel training can be made significantly more efficient by sharding the model parameters and optimizer state across data parallel workers. -
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AI Atelier
Based on the Disco Diffusion, version of the AI art creation software
Based on the Disco Diffusion, we have developed a Chinese & English version of the AI art creation software "AI Atelier". We offer both Text-To-Image models (Disco Diffusion and VQGAN+CLIP) and Text-To-Text (GPT-J-6B and GPT-NEOX-20B) as options. Making available complete source code of licensed works and modifications, which include larger works using a licensed work, under the same license. Copyright and license notices must be preserved. When a modified version is used to provide a... -
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Tensorflow Transformers
State of the art faster Transformer with Tensorflow 2.0
Imagine auto-regressive generation to be 90x faster. tf-transformers (Tensorflow Transformers) is designed to harness the full power of Tensorflow 2, designed specifically for Transformer based architecture. These models can be applied on text, for tasks like text classification, information extraction, question answering, summarization, translation, text generation, in over 100 languages. Images, for tasks like image classification, object detection, and segmentation. Audio, for tasks like speech recognition and audio classification. Faster AutoReggressive Decoding, TFlite support, creating TFRecords is simple. Auto-Batching tf.data.dataset or tf.ragged tensors. Everything is dictionary (inputs and outputs) Multiple mask modes like causal, user-defined, prefix. tensorflow-text tokenizer support. ... -
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Kaplan Desktop
Free and open-source CAT tool for linguists
A free and open-source computer-assisted translation tool built with Django/Python and Electronjs/Nodejs. For the relevant repositories, please see https://github.com/kaplanPRO kaplanpy currently handles the following doctypes: • .docx • .odp • .ods • .odt • .txt • .xliff (very limited coverage) • .po -
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ADFILT
Web filter lists for countless different topics
This is the place where I, Imre Kristoffer Eilertsen, host my web filter lists for countless different topics, for use in adblock tools and the like. GitHub was in mid-2017 by far the easiest way for laymen like me to store pure text files, which is a necessity to create subscribable lists. This is a hobby project of mine, in which I work just as much on these lists and this repo as I feel like. But don't be fooled by the appearance, as these are nevertheless some lists that I've placed lots... -
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PaddleGAN
PaddlePaddle GAN library, including lots of interesting applications
PaddlePaddle GAN library, including lots of interesting applications like First-Order motion transfer, Wav2Lip, picture repair, image editing, photo2cartoon, image style transfer, GPEN, and so on. PaddleGAN provides developers with high-performance implementation of classic and SOTA Generative Adversarial Networks, and supports developers to quickly build, train and deploy GANs for academic, entertainment, and industrial usage. GAN-Generative Adversarial Network, was praised by "the Father... -
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Argos Translate
Open-source offline translation library written in Python
Argos Translate uses OpenNMT for translations and can be used as either a Python library, command-line, or GUI application. Argos Translate supports installing language model packages which are zip archives with a ".argosmodel" extension containing the data needed for translation. LibreTranslate is an API and web-app built on top of Argos Translate. Argos Translate also manages automatically pivoting through intermediate languages to translate between languages that don't have a direct translation between them installed. For example, if you have a es → en and en → fr translation installed you are able to translate from es → fr as if you had that translation installed. ... -
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DeepImageTranslator
DeepImageTranslator: a deep-learning utility for image translation
Created by: Run Zhou Ye, En Zhou Ye, and En Hui Ye DeepImageTranslator: a free, user-friendly tool for image translation using deep-learning and its applications in CT image analysis Citation: Please cite this software as: Ye RZ, Noll C, Richard G, Lepage M, Turcotte ÉE, Carpentier AC. DeepImageTranslator: a free, user-friendly graphical interface for image translation using deep-learning and its applications in 3D CT image analysis. SLAS technology. 2022 Feb 1;27(1):76-84. https://doi.org/10.1016/j.slast.2021.10.014 -
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Old Photo Restoration
Bringing Old Photo Back to Life (CVPR 2020 oral)
...Unlike conventional restoration tasks that can be solved through supervised learning, the degradation in real photos is complex and the domain gap between synthetic images and real old photos makes the network fail to generalize. Therefore, we propose a novel triplet domain translation network by leveraging real photos along with massive synthetic image pairs. Specifically, we train two variational autoencoders (VAEs) to respectively transform old photos and clean photos into two latent spaces. And the translation between these two latent spaces is learned with synthetic paired data. This translation generalizes well to real photos because the domain gap is closed in the compact latent space. ... -
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Pytago
A source-to-source transpiler for Python to Go translation
pytago is a source-to-source transpiler that converts some Python into human-readable Go. It enables developers to translate Python codebases into Go, facilitating migration or interoperability between the two languages. -
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DeepMosaics
Automatically remove the mosaics in images and videos, or add mosaics
Automatically remove the mosaics in images and videos, or add mosaics to them. This project is based on "semantic segmentation" and "Image-to-Image Translation". You can either run DeepMosaics via a pre-built binary package, or from source. Run time depends on the computer's performance (GPU version has better performance but requires CUDA to be installed). Different pre-trained models are suitable for different effects.[Introduction to pre-trained models]. -
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SRU
Training RNNs as Fast as CNNs
...SRU achieves 5--9x speed-up over cuDNN-optimized LSTM on classification and question answering datasets, and delivers stronger results than LSTM and convolutional models. We also obtain an average of 0.7 BLEU improvement over the Transformer model on the translation by incorporating SRU into the architecture. The experimental code and SRU++ implementation are available on the dev branch which will be merged into master later. -
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XLM (Cross-lingual Language Model)
PyTorch original implementation of Cross-lingual Language Model
XLM (Cross-lingual Language Model) is a family of multilingual pretraining methods that align representations across languages to enable strong zero-shot transfer. It popularized objectives like Masked Language Modeling (MLM) across many languages and Translation Language Modeling (TLM) that jointly trains on parallel sentence pairs to tighten cross-lingual alignment. Using a shared subword vocabulary, XLM learns language-agnostic features that work well for classification and sequence labeling tasks such as XNLI, NER, and POS without target-language supervision. The repository provides preprocessing pipelines, training code, and fine-tuning scripts so you can reproduce benchmark results or adapt models to your own multilingual corpora. ... -
20
onnxt5
Summarization, translation, sentiment-analysis, text-generation, etc.
Summarization, translation, sentiment analysis, text-generation and more at blazing speed using a T5 version implemented in ONNX. This package is still in the alpha stage, therefore some functionalities such as beam searches are still in development. The simplest way to get started for generation is to use the default pre-trained version of T5 on ONNX included in the package. -
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Linkedin Skill assessments
Full reference of LinkedIn answers 2023 for skill assessments
This repository is for those looking for answers to the LinkedIn assessment quiz questions or willing to help others by contributing to the tests. Or possibly you would like to create your first pull request and be added as a contributor. Add an explanation (or reference link) to your answers. That will help anyone to better learn concepts they might not have a great understanding of. Your resource for answers. In case you have doubts please contact this person or add them to review your PR. -
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MachineTrans
A prototype for a Russian-English machine translation program.
This program currently allows for input of vocabulary an generation of random English sentences from semi-random data. -
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Multilingual Speech Synthesis
An implementation of Tacotron 2 that supports multilingual experiments
...It presents a model combining ideas from Learning to speak fluently in a foreign language: Multilingual speech synthesis and cross-language voice cloning, End-to-End Code-Switched TTS with Mix of Monolingual Recordings, and Contextual Parameter Generation for Universal Neural Machine Translation. We provide data for comparison of three multilingual text-to-speech models. The first shares the whole encoder and uses an adversarial classifier to remove speaker-dependent information from the encoder. The second has separate encoders for each language. -
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Spaceship Generator
A Blender script to procedurally generate 3D spaceships
...Expand the Spaceship tab that appears in the bottom left of the viewport to adjust procedural generation settings. Build the hull. Extrude the front/rear faces several times, adding random translation/scaling/rotation along the way. Add asymmetry to the hull: Pick random faces and extrude them out in a similar manner, reducing in scale each time. Categorize each face by its orientation and generate details on it such as engines, antenna, weapon turrets, lights etc. -
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NLP-Models-Tensorflow
Gathers machine learning and Tensorflow deep learning models for NLP
...The repository provides numerous examples of neural network architectures used in modern NLP research and applications, including text classification, language modeling, machine translation, and sentiment analysis. Each model implementation is designed to illustrate how common NLP architectures operate, such as recurrent neural networks, convolutional models for text processing, and transformer-style attention mechanisms. The project includes scripts for preparing datasets, training models, and evaluating performance on various text analysis tasks. ...
