imagen-pytorch
tortoise-tts
imagen-pytorch | tortoise-tts | |
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47 | 145 | |
7,787 | 11,819 | |
- | - | |
6.8 | 8.0 | |
29 days ago | about 23 hours ago | |
Python | Jupyter Notebook | |
MIT License | Apache License 2.0 |
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imagen-pytorch
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Google's StyleDrop can transfer style from a single image
If google doesnt, someone like lucidrains probably would implement it, just like he did for imagen and muse.
- Create a Stable diffusion neural network from scratch.
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Google just announced an Even better diffusion process.
lucidrains/imagen-pytorch: Implementation of Imagen, Google's Text-to-Image Neural Network, in Pytorch (github.com)
- Karlo, the first large scale open source DALL-E 2 replication is here
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training imagen
Hi Can someone guide me a little, as to how i can use LAION dataset to train my imagen model? like how i can download the data, and in which format it should be fed to https://github.com/lucidrains/imagen-pytorch code?
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If everyone in this sub make a donation of $10 then we can train truly open stable diffusion.
If we were to put money into training something, I'd hope we use a better model, like Imagen.
- AI Content Generation, Part 1: Machine Learning Basics
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DALL-E 2 is switching to a credits system (50 generations for free at first, 15 free per month)
I've been messing around with this open-source implementation. You can get a pretty good idea of the model size by just copying the parameters from the paper.
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Protests erupt outside of DALL-E offices after pricing implementation, press photograph
I'm waiting on this implementation/training of imagen: https://github.com/lucidrains/imagen-pytorch
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Show HN: Food Does Not Exist
I'm honestly surprised that they trained a StyleGAN. Recently, the Imagen architecture has been show to be both easier in structure, easier to train, and even faster to produce good results. Combined with the "Elucidating" paper by NVIDIA's Tero Karras you can train a 256px Imagen to tolerable quality within an hour on a RTX 3090.
Here's a PyTorch implementation by the LAION people:
https://github.com/lucidrains/imagen-pytorch
And here's 2 images I sampled after training it for some hours, like 2 hours base model + 4 hours upscaler:
https://imgur.com/a/46EZsJo
tortoise-tts
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ESpeak-ng: speech synthesizer with more than one hundred languages and accents
The quality also depends on the type of model. I'm not really sure what ESpeak-ng actually uses? The classical TTS approaches often use some statistical model (e.g. HMM) + some vocoder. You can get to intelligible speech pretty easily but the quality is bad (w.r.t. how natural it sounds).
There are better open source TTS models. E.g. check https://github.com/neonbjb/tortoise-tts or https://github.com/NVIDIA/tacotron2. Or here for more: https://www.reddit.com/r/MachineLearning/comments/12kjof5/d_...
- FLaNK Stack Weekly 12 February 2024
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OpenVoice: Versatile Instant Voice Cloning
I use Tortoise TTS. It's slow, a little clunky, and sometimes the output gets downright weird. But it's the best quality-oriented TTS I've found that I can run locally.
https://github.com/neonbjb/tortoise-tts
- [discussion] text to voice generation for textbooks
- DALL-E 3: Improving image generation with better captions [pdf]
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Open Source Libraries
neonbjb/tortoise-tts
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Running Tortoise-TTS - IndexError: List out of range
EDIT: It appears to be the exact same issue as this
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My Deep Learning Rig
It was primarily being used to train TTS models (see https://github.com/neonbjb/tortoise-tts), which largely fit into a single GPUs memory. So, for data parallelism, x8 PCIe isn't that much of a concern.
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PlayHT2.0: State-of-the-Art Generative Voice AI Model for Conversational Speech
Previously TortoiseTTS was associated with PlayHT in some way, although the exact connection is a bit vague [0].
From the descriptions here it sounds a lot like AudioLM / SPEAR TTS / some of Meta's recent multilingual TTS approaches, although those models are not open source, sounds like PlayHT's approach is in a similar spirit. The discussion of "mel tokens" is closer to what I would call the classic TTS pipeline in many ways... PlayHT has generally been kind of closed about what they used, would be interesting to know more.
I assume the key factor here is high quality, emotive audio with good data cleaning processes. Probably not even a lot of data, at least in the scale of "a lot" in speech, e.g. ASR (millions of hours) or TTS (hundreds to thousands). As opposed to some radically new architectural piece never before seen in the literature, there are lots of really nice tools for emotive and expressive TTS buried in recent years of publications.
Tacotron 2 is perfectly capable of this type of stuff as well, as shown by Dessa [1] a few years ago (this writeup is a nice intro to TTS concepts). With the limit largely being, at some point you haven't heard certain phonetic sounds before in a voice, and need to do something to get plausible outcomes for new voices.
[0] Discussion here https://github.com/neonbjb/tortoise-tts/issues/182#issuecomm...
[1] https://medium.com/dessa-news/realtalk-how-it-works-94c1afda...
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Comparing Tortoise and Bark for Voice Synthesis
Tortoise GitHub repo - Source code, documentation, and usage guide
What are some alternatives?
dalle-mini - DALL·E Mini - Generate images from a text prompt
TTS - 🐸💬 - a deep learning toolkit for Text-to-Speech, battle-tested in research and production
DALLE2-pytorch - Implementation of DALL-E 2, OpenAI's updated text-to-image synthesis neural network, in Pytorch
bark - 🔊 Text-Prompted Generative Audio Model
DALLE-pytorch - Implementation / replication of DALL-E, OpenAI's Text to Image Transformer, in Pytorch
Real-Time-Voice-Cloning - Clone a voice in 5 seconds to generate arbitrary speech in real-time
latent-diffusion - High-Resolution Image Synthesis with Latent Diffusion Models
piper - A fast, local neural text to speech system
DeepCreamPy - deeppomf's DeepCreamPy + some updates
tacotron2 - Tacotron 2 - PyTorch implementation with faster-than-realtime inference
CogVideo - Text-to-video generation. The repo for ICLR2023 paper "CogVideo: Large-scale Pretraining for Text-to-Video Generation via Transformers"
larynx - End to end text to speech system using gruut and onnx