whisper
stable-diffusion
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whisper | stable-diffusion | |
---|---|---|
343 | 382 | |
60,303 | 65,389 | |
5.9% | 2.2% | |
6.4 | 0.0 | |
15 days ago | 13 days ago | |
Python | Jupyter Notebook | |
MIT License | GNU General Public License v3.0 or later |
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.
whisper
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Why I Care Deeply About Web Accessibility And You Should Too
Let’s not talk about local models as the hardware requirements are way beyond most of these people’s reach. I have a MacBook Air with an M2 chip and 8GB of RAM and can hardly run Whisper locally, so I use this HuggingFace space.
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How I built NotesGPT – a full-stack AI voice note app
Last week, I launched notesGPT, a free and open source voice note app that has 35,000 visitors, 7,000 users, and over 1,000 GitHub stars so far in the last week. It allows you to record a voice note, transcribes it uses Whisper, and uses Mixtral via Together to extract action items and display them in an action items view. It’s also fully open source and comes equipped with authentication, storage, vector search, action items, and is fully responsive on mobile for ease of use.
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Ask HN: Can AI break a speech audio into individual words?
I found a pretty good discussion in the topic here:
https://github.com/openai/whisper/discussions/1243
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WhisperSpeech – An Open Source text-to-speech system built by inverting Whisper
There is a plot of language performance on their repo: https://github.com/openai/whisper
I am not aware of a multi-lingual leaderboard for speech recognition models.
- Ask HN: AI that allows you to make phone calls in a language you don't speak?
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Ask HN: Favorite Podcast Episodes of 2023?
I don't know how OP does it, but here's how I'd do it:
* Generate a transcript by runing Whisper against the podcast audio file: https://github.com/openai/whisper
* Upload transcript to ChatGPT and ask it to summarize.
* Automate all the above.
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Need advice
Ahh, that makes sense. I've been building something like that, but only from other languages into English using Whisper
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Subtitle is now open-source
Whisper already generates subtitles[0], supporting VTT and SRT so this is just a thin wrapper around that.
[0]: https://github.com/openai/whisper/blob/e58f28804528831904c3b...
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StyleTTS2 – open-source Eleven Labs quality Text To Speech
> although it does require you to wear headphones so the bot doesn't hear itself and get interrupted.
Maybe you can rely on some sort of speaker identification to sort this out?
https://github.com/openai/whisper/discussions/264
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Federated Finetuning of OpenAI's Whisper on Raspberry Pi 5
v3 only comes in one flavor: large.
I don’t think you’re going to have a good time running the large model on a Pi of any kind.
The large models are 32x slower than the tiny models, roughly.[0]
I’m seeing people report that the Pi 4 can transcribe 30 seconds of audio in somewhere between 30 seconds and 60 seconds with the tiny model.
You can do the math… 32x = 16 minutes to 32 minutes to transcribe 30 seconds of audio with the large model. Not a good time for most people.
The Pi 5 could be 2x to 3x faster.
I should benchmark my Pi 4 sometime (or Pi 5, if it ever shows up).
[0]: https://github.com/openai/whisper/blob/main/README.md#availa...
stable-diffusion
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Go is bigger than crab!
Which is a 1-click install of Stable Diffusion with an alternative web interface. You can choose a different approach but this one is pretty simple and I am new to this stuff.
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Why & How to check Invisible Watermark
an invisible watermarking of the outputs, to help viewers identify the images as machine-generated.
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How to create an Image generating AI?
It sounds like you just want to set up Stable Diffusion to run locally. I don't think your computer's specs will be able to do it. You need a graphics card with a decent amount of VRAM. Stable diffusion is in Python as is almost every AI open source project I've seen. If you can get your hands on a system with an Nvidia RTX card with as much VRAM as possible, you're in business. I have an RTX 3060 with 12 gigs of VRAM and I can run stable diffusion and a whole variety of open source LLMs as well as other projects like face swap, Roop, tortoise TTS, sadtalker, etc...
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Two video cards...one dedicated to Stable Diffusion...the other for everything else on my PC?
Use specific GPU on multi GPU systems · Issue #87 · CompVis/stable-diffusion · GitHub
- Automatic1111 - Multiple GPUs
- Ist Google inzwischen einfach unbrauchbar?
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Why are people so against compensation for artists?
I dealt with this in one of my posts. At least SD 1.1 till 1.5 are all trained on a batch size of 2048. The version pretty much everyone uses (1.5) is first pretrained at a resolution of 256x256 for 237K steps on laion2B-en, at the end of those training steps it will have seen roughly 500M images in laion2B-en. After that it is pre-trained for 194K steps on laion-high-resolution at a resolution of 512x512, which is a subset of 170M images from laion5B. Finally it is trained for 1.110K steps on LAION aesthetic v2 5+. This is easily verified by taking a glance at the model card of SD 1.5. Though that one doesn't specify for part of the training exactly which aesthetic set was used for part of the training, for that you have to look at the CompVis github repo. Thus at the end of it all both the most recent images and the majority of images will have come from LAION aesthetic v2 5+ (seeing every image approx 4 times). Realistically a lot of the weights obtained from pretraining on 2B will have been lost, and only provided a good starting point for the weights.
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Is SDXL really open-source?
stable diffusion · CompVis/stable-diffusion@2ff270f · GitHub
- I want to ask the AI to draw me as a Pokemon anime character then draw six of Pokemon of my choice next to me. What are my best free, 15$ or under and 30$ or under choices?
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how can i create my own ai image model
Here for example --> https://github.com/CompVis/stable-diffusion
What are some alternatives?
vosk-api - Offline speech recognition API for Android, iOS, Raspberry Pi and servers with Python, Java, C# and Node
GFPGAN - GFPGAN aims at developing Practical Algorithms for Real-world Face Restoration.
silero-vad - Silero VAD: pre-trained enterprise-grade Voice Activity Detector
Real-ESRGAN - Real-ESRGAN aims at developing Practical Algorithms for General Image/Video Restoration.
buzz - Buzz transcribes and translates audio offline on your personal computer. Powered by OpenAI's Whisper.
diffusers-uncensored - Uncensored fork of diffusers
NeMo - A scalable generative AI framework built for researchers and developers working on Large Language Models, Multimodal, and Speech AI (Automatic Speech Recognition and Text-to-Speech)
diffusers - 🤗 Diffusers: State-of-the-art diffusion models for image and audio generation in PyTorch and FLAX.
whisper.cpp - Port of OpenAI's Whisper model in C/C++
VQGAN-CLIP - Just playing with getting VQGAN+CLIP running locally, rather than having to use colab.
text-generation-webui - A Gradio web UI for Large Language Models. Supports transformers, GPTQ, AWQ, EXL2, llama.cpp (GGUF), Llama models.
onnx - Open standard for machine learning interoperability