Opus-MT
TheAlgorithms
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Opus-MT | TheAlgorithms | |
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3 | 61 | |
527 | 179,554 | |
8.7% | 1.9% | |
4.8 | 9.7 | |
3 days ago | 4 days ago | |
Python | Python | |
MIT License | MIT License |
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For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
Opus-MT
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“sync,corrected by elderman” issue in ML translation datasets spread on internet
- mention on GitHub repo of a translation model https://github.com/Helsinki-NLP/Opus-MT/issues/62
I'm curious to see if anyone else has interesting encounters with this
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How worried are you about AI taking over music?
Yes, most models these days, except the exceptionally large ones, are possible to train on a laptop. Of course it helps if your laptop has Nvidia CUDA GPU, but even if it doesn't you can rent an AWS 4 core/16GB GPU instance for 0.5 cents an hour. 24 hours of training time would be quite a lot for most models, unless you're trying to train a FB any to any language type model, but typically the big huge models are not the most interesting ones, and you can get very good results, and interesting models with substantially smaller sets of data. Opus MT models are only one language to one language, but they're about 300MB a model, and the quality rivals FB's models, and the speed is substantially faster. I don't have as many examples from the music space, as it's still a fairly under explored area, but Google has released Magenta which is a pretrained Tensorflow music model(actually a group of 3-4 models).
- Helsinki-NLP/Opus-MT: Open neural machine translation models and web services
TheAlgorithms
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Wikifunctions
Is it me or does it not seem very well thought out? Every example I've seen only has implementations in JavaScript and/or Python. I haven't seen any other languages nor a way to search by language. What a "string" means in one language can be completely different in another language. The primitive data types that the project assumes are not really supported across all programming languages.
Also if anyone hasn't already seen them, similar projects already exist and are more complete. E.g.
* https://rosettacode.org/
* https://programming-idioms.org/
* https://the-algorithms.com/
Not to mention LeetCode, CodeWars, Project Euler, Exercism can kinda serve the same role.
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Introduction
Hey Everyone, My name is Rachit Chawla and Its my first blog on dev.to. I am currently a student of Computer Programming and Analysis at Seneca College. Also I'm currently on my co-op term working as an Automation Developer at Ontario Public Service. In this role, I am currently working with PowerShell scripting and Microsoft Azure for automating every manual tasks to reduce workload and increase efficiency. This blog is a part of OSD600 course at Seneca College. I am taking this course as I am big fan of open source and always wanted to contribute in open source projects but I am unaware of proper documentation and standards used for open source contributions. I am hoping to learn all the required stuff by the end of this course and I aim to be one of the 15k contributors to Linux's repo by Linus Torvald. Open Source interests me because it gives developers the power to customise the application they want to use, also a chance to help others and improve their skills. I found https://github.com/TheAlgorithms/Python interesting from the Monthly trending feed on Github as it has all the algorithms which help us improve time complexity and write better codes. I has about 1000 contributors which helped to code all the algorithms in Python which may help others for working or learning purposes. I myself was a student of Data Structures and Algorithms in Python Winter 2023 and hoping to even able to contribute to this repo itself, once I learn more about documentation & proper standards to be followed.
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I am studying my college Python so can I learn algorithms from it?
The Algorithms Contains many open source implementations of algorithms. Check it out.
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Where To Read About Python Algos?
If you want to see implementations of all possible traversal algorithms you can find it here.
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Book of pythonic code
The mother load of all algorithms in python is here. dfs/bfs in particular are in the graph section.
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Any tips to improve my coding abilites ?
There is no one way to learn all these but here are some resources: 1. Gooking algorithms [https://edu.anarcho-copy.org/Algorithm/grokking-algorithms-illustrated-programmers-curious.pdf\] 2. Algorithms in all languages [https://the-algorithms.com/] 3. Node js best practices. [https://github.com/goldbergyoni/nodebestpractices] 4. Refactoring [https://refactoring.guru/] 5. Learn about Clean Code and Clean Architecture from uncle bob. https://www.youtube.com/watch?v=NeXQEJNWO5w&ab_channel=StreamAConStreamingConferences
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Self taught developers: where are you in your journey?
DSA basics
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Algo and data structures
I would recommend The Algorithms, it comes with descriptions and examples in multiple programming languages.
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A site that hosts implementations of various programming algorithms in different languages
There's also The Algorithms. Many implementations are unfortunately low quality. The Lua ones (disclaimer: I wrote them) should be fine however.
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How worried are you about AI taking over music?
Python 940 contributors 152k stars
What are some alternatives?
OPUS-MT-train - Training open neural machine translation models
python-ds - No non-sense and no BS repo for how data structure code should be in Python - simple and elegant.
OpenNMT-py - Open Source Neural Machine Translation and (Large) Language Models in PyTorch
new-world-fishing-bot - user friendly python script who is able to catch fish in the game New World
fastText - Library for fast text representation and classification.
python-patterns - A collection of design patterns/idioms in Python
Neural-Machine-Translated-communication-system - The model is designed to train a single and large neural network in order to predict correct translation by reading the given sentence.
algorithms
tensor2tensor - Library of deep learning models and datasets designed to make deep learning more accessible and accelerate ML research.
more-itertools - More routines for operating on iterables, beyond itertools
Pytorch - Tensors and Dynamic neural networks in Python with strong GPU acceleration
ClointFusion - Cloint India Pvt. Ltd's (ClointFusion) Pythonic RPA (Automation) Platform