bark
text-generation-webui
bark | text-generation-webui | |
---|---|---|
67 | 876 | |
32,784 | 36,552 | |
3.8% | - | |
5.4 | 9.9 | |
7 days ago | 6 days ago | |
Jupyter Notebook | Python | |
MIT License | GNU Affero General Public License v3.0 |
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bark
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Exploring Bark, the Open Source Text-to-Speech Model
!pip install git+https://github.com/suno-ai/bark.git
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AI-generated sad girl with piano performs the text of the MIT License
To my knowledge, the model being used for this is "chirp" which is 'based on' bark[1], an AI text to speech model.
The github page for bark links to a page about chirp, which returns a 404 page for me [2]. that the model for suno.ai's song generator isn't too much different than the text to speech model.
My hunch is that it was something like a coincidence that the bark model was capable of producing music, and that was spun off into this product. Unfortunately, there seems to still be issues with bark when generating long (like book length) spoken audio. Which is too bad, as someone who's worked jobs that require lots of driving, it would be awesome to be able to have any text read to me in a natural sounding voice.
[1]https://github.com/suno-ai/bark
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Generating music in the waveform domain (2020)
Stable-audio and MusicGen sounds better than Jukebox.
But the best so far is Suno.ai ( https://app.suno.ai ) especially with their V3 model they have very impressive results, the fidelity is not studio quality but they're getting very close.
It's very likely based on their TTS model they have released before Bark, but trained on more data and with higher resolution.
https://github.com/suno-ai/bark
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Stable-Audio-Demo
https://github.com/suno-ai/bark
> Bark was developed for research purposes. It is not a conventional text-to-speech model but instead a fully generative text-to-audio model, which can deviate in unexpected ways from provided prompts. Suno does not take responsibility for any output generated. Use at your own risk, and please act responsibly.
I've generated probably >200 songs now with Suno, of which perhaps 10 have been any good, and I can't detect any pattern in terms of the outputs.
Here's another one which is pretty good. I accidentally copied and pasted the prompt and lyrics, and it's amazing to me how 'musically' it renders the prompt:
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Suno AI
hahah wow! cool :-)
PS: OT, I am reading this Bark thing(https://github.com/suno-ai/bark). Can I run it locally on a Macbook 2015 with 8GB RAM?
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SDXL + SVD + Suno AI
I have it locally. The model is on huggingface. It runs with about 8GB VRAM.
- [discussion] text to voice generation for textbooks
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Open Source Libraries
suno-ai/bark
- Weird A.I. Yankovic, a cursed deep dive into the world of voice cloning
- FLaNK Stack Weekly 2 October 2023
text-generation-webui
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Ask HN: What is the current (Apr. 2024) gold standard of running an LLM locally?
Some of the tools offer a path to doing tool use (fetching URLs and doing things with them) or RAG (searching your documents). I think Oobabooga https://github.com/oobabooga/text-generation-webui offers the latter through plugins.
Our tool, https://github.com/transformerlab/transformerlab-app also supports the latter (document search) using local llms.
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Ask HN: How to get started with local language models?
You can use webui https://github.com/oobabooga/text-generation-webui
Once you get a version up and running I make a copy before I update it as several times updates have broken my working version and caused headaches.
a decent explanation of parameters outside of reading archive papers: https://github.com/oobabooga/text-generation-webui/wiki/03-%...
a news ai website:
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text-generation-webui VS LibreChat - a user suggested alternative
2 projects | 29 Feb 2024
- Show HN: I made an app to use local AI as daily driver
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Ask HN: People who switched from GPT to their own models. How was it?
The other answers are recommending paths which give you #1. less control and #2. projects with smaller eco-systems.
If you want a truly general purpose front-end for LLMs, the only good solution right now is oobabooga: https://github.com/oobabooga/text-generation-webui
All other alternatives have only small fractions of the features that oobabooga supports. All other alternatives only support a fraction of the LLM backends that oobabooga supports, etc.
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AI Girlfriend Is a Data-Harvesting Horror Show
The example waifu in text-generation-webui is good enough for me.
https://github.com/oobabooga/text-generation-webui/blob/main...
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Nvidia's Chat with RTX is a promising AI chatbot that runs locally on your PC
> Downloading text-generation-webui takes a minute, let's you use any model and get going.
What you're missing here is you're already in this area deep enough to know what ooogoababagababa text-generation-webui is. Let's back out to the "average Windows desktop user" level. Assuming they even know how to find it:
1) Go to https://github.com/oobabooga/text-generation-webui?tab=readm...
2) See a bunch of instructions opening a terminal window and running random batch/powershell scripts. Powershell, etc will likely prompt you with a scary warning. Then you start wondering who ooobabagagagaba is...
3) Assuming you get this far (many users won't even get to step 1) you're greeted with a web interface[0] FILLED to the brim with technical jargon and extremely overwhelming options just to get a model loaded, which is another mind warp because you get to try to select between a bunch of random models with no clear meaning and non-sensical/joke sounding names from someone called "TheBloke". Ok...
Let's say you somehow braved this gauntlet and get this far now you get to chat with it. Ok, what about my local documents? text-generation-webui itself has nothing for that. Repeat this process over the 10 random open source projects from a bunch of names you've never heard of in an attempt to accomplish that.
This is "I saw this thing from Nvidia explode all over media, twitter, youtube, etc. I downloaded it from Nvidia, double-clicked, pointed it at a folder with documents, and it works".
That's the difference and it's very significant.
[0] - https://raw.githubusercontent.com/oobabooga/screenshots/main...
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Ask HN: What are your top 3 coolest software engineering tools?
Maybe a copout answer, but setting up a local LLM on my development machine has been invaluable. I use Deep Seek Coder 6.7 [0] and Oobabooga's UI [1]. It helps me solve simple problems and find bugs, while still leaving the larger architecture decisions to me.
[0] https://huggingface.co/deepseek-ai/deepseek-coder-6.7b-instr...
[1] https://github.com/oobabooga/text-generation-webui
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Meta AI releases Code Llama 70B
You can download it and run it with [this](https://github.com/oobabooga/text-generation-webui). There's an API mode that you could leverage from your VS Code extension.
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Ollama Python and JavaScript Libraries
Same question here. Ollama is fantastic as it makes it very easy to run models locally, But if you already have a lot of code that processes OpenAI API responses (with retry, streaming, async, caching etc), it would be nice to be able to simply switch the API client to Ollama, without having to have a whole other branch of code that handles Alama API responses. One way to do an easy switch is using the litellm library as a go-between but it’s not ideal (and I also recently found issues with their chat formatting for mistral models).
For an OpenAI compatible API my current favorite method is to spin up models using oobabooga TGW. Your OpenAI API code then works seamlessly by simply switching out the api_base to the ooba endpoint. Regarding chat formatting, even ooba’s Mistral formatting has issues[1] so I am doing my own in Langroid using HuggingFace tokenizer.apply_chat_template [2]
[1] https://github.com/oobabooga/text-generation-webui/issues/53...
[2] https://github.com/langroid/langroid/blob/main/langroid/lang...
Related question - I assume ollama auto detects and applies the right chat formatting template for a model?
What are some alternatives?
tortoise-tts - A multi-voice TTS system trained with an emphasis on quality
KoboldAI - KoboldAI is generative AI software optimized for fictional use, but capable of much more!
SadTalker - [CVPR 2023] SadTalker:Learning Realistic 3D Motion Coefficients for Stylized Audio-Driven Single Image Talking Face Animation
llama.cpp - LLM inference in C/C++
Retrieval-based-Voice-Conversion-WebUI - Easily train a good VC model with voice data <= 10 mins!
gpt4all - gpt4all: run open-source LLMs anywhere
whisper.cpp - Port of OpenAI's Whisper model in C/C++
TavernAI - Atmospheric adventure chat for AI language models (KoboldAI, NovelAI, Pygmalion, OpenAI chatgpt, gpt-4)
TTS - 🐸💬 - a deep learning toolkit for Text-to-Speech, battle-tested in research and production
KoboldAI-Client
audiolm-pytorch - Implementation of AudioLM, a SOTA Language Modeling Approach to Audio Generation out of Google Research, in Pytorch
ollama - Get up and running with Llama 3, Mistral, Gemma, and other large language models.