RAVE
spaCy
RAVE | spaCy | |
---|---|---|
9 | 106 | |
1,201 | 28,751 | |
- | 0.6% | |
7.7 | 9.2 | |
12 days ago | 6 days ago | |
Python | Python | |
GNU General Public License v3.0 or later | MIT License |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
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.
RAVE
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How could you use AI for music inspiration/ideas?
Also, theres new tools like https://github.com/acids-ircam/RAVE which can be used to create new sounds, i feel like the more granular you work with AI on art, the better can help you out. Magentajs is pretty cool! Im still just playing with it but is easy to use so far.
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Sonification of particles coordinates
https://github.com/acids-ircam/RAVE hope this wasn't too much off topic, i'm just super enthusiastic about RAVE and have been trying to squeeze a sonification in with it with no good applications so far. this feels kinda awesome tho. maybe it fits?
- Zero coding experience, trying to setup a training environment and running into an error
- I train some models, but GPU usage is too low is that normal for learning a model in local?
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Ask HN: What weird technical scene are you fond/part of?
I'm in the deep learning music scene, which is due for its stable diffusion moment in the next year or two. The (primarily) timbre transfer system called RAVE is where I'm starting, and my contribution is to optimize the system to improve training time.
[] https://github.com/acids-ircam/RAVE/tree/master/rave
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Hello
I'm obsessed with generative audio models, particularly RAVE[0].
Music is set to have its GPT-3 / Stable Diffusion moment within a couple years.
I believe in 10 years the venn diagram of music made with computers and music made with neural nets will be a circle, and that now is a great time to jump in.
Would LOVE to swap notes with anyone else here into this. Email in bio.
[0] https://github.com/acids-ircam/RAVE
- Rave: Realtime Audio Variational AutoEncoder
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[D] What is state of the art for audio generation?
Source code is here: https://github.com/caillonantoine/RAVE
spaCy
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Step by step guide to create customized chatbot by using spaCy (Python NLP library)
Hi Community, In this article, I will demonstrate below steps to create your own chatbot by using spaCy (spaCy is an open-source software library for advanced natural language processing, written in the programming languages Python and Cython):
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Best AI SEO Tools for NLP Content Optimization
SpaCy: An open-source library providing tools for advanced NLP tasks like tokenization, entity recognition, and part-of-speech tagging.
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Who has the best documentation you’ve seen or like in 2023
spaCy https://spacy.io/
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A beginner’s guide to sentiment analysis using OceanBase and spaCy
In this article, I'm going to walk through a sentiment analysis project from start to finish, using open-source Amazon product reviews. However, using the same approach, you can easily implement mass sentiment analysis on your own products. We'll explore an approach to sentiment analysis with one of the most popular Python NLP packages: spaCy.
- Retrieval Augmented Generation (RAG): How To Get AI Models Learn Your Data & Give You Answers
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Against LLM Maximalism
Spacy [0] is a state-of-art / easy-to-use NLP library from the pre-LLM era. This post is the Spacy founder's thoughts on how to integrate LLMs with the kind of problems that "traditional" NLP is used for right now. It's an advertisement for Prodigy [1], their paid tool for using LLMs to assist data labeling. That said, I think I largely agree with the premise, and it's worth reading the entire post.
The steps described in "LLM pragmatism" are basically what I see my data science friends doing — it's hard to justify the cost (money and latency) in using LLMs directly for all tasks, and even if you want to you'll need a baseline model to compare against, so why not use LLMs for dataset creation or augmentation in order to train a classic supervised model?
[0] https://spacy.io/
[1] https://prodi.gy/
- Swirl: An open-source search engine with LLMs and ChatGPT to provide all the answers you need 🌌
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How to predict this sequence?
spaCy
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What do you all think about (setq sentence-end-double-space nil)?
I chose spacy. Although it's not state of the art, it's very well established and stable.
- spaCy: Industrial-Strength Natural Language Processing
What are some alternatives?
denoising-diffusion-pytorch - Implementation of Denoising Diffusion Probabilistic Model in Pytorch
TextBlob - Simple, Pythonic, text processing--Sentiment analysis, part-of-speech tagging, noun phrase extraction, translation, and more.
Spectrum - Spectrum is an AI that uses machine learning to generate Rap song lyrics
Stanza - Stanford NLP Python library for tokenization, sentence segmentation, NER, and parsing of many human languages
LibreQoS - A Quality of Experience and Smart Queue Management system for ISPs. Leverage CAKE to improve network responsiveness, enforce bandwidth plans, and reduce bufferbloat.
NLTK - NLTK Source
rvc - A 32-bit RISC-V emulator in a shader (and C)
BERT-NER - Pytorch-Named-Entity-Recognition-with-BERT
Speed-Run-Sidebar - A Display + Controller to integrate with OBS
polyglot - Multilingual text (NLP) processing toolkit
SVM-Face-and-Object-Detection-Shader - SVM using HOG descriptors implemented in fragment shaders
textacy - NLP, before and after spaCy