tinygrad
mac-precision-touchpad
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tinygrad | mac-precision-touchpad | |
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17 | 100 | |
23,232 | 8,427 | |
4.8% | - | |
9.9 | 0.0 | |
3 days ago | 3 months ago | |
Python | C | |
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.
tinygrad
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AMD Unveils Ryzen 8000G Series Processors: Zen 4 APUs for Desktop with Ryzen AI
Not sure if I completely understand what "Ryzen AI" does, but Tinygrad for example has some limited support for RDNA3[0]. It isn't quite there yet in matters of performance though, as you can read in the comments of that file.
There's also a small tutorial by AMD on how to use the WMMA intrinsic[1] using AMD's hipcc[2] compiler. Documentation is sparse kinda sparse, but the instruction set is not huge. The RDNA3 ISA guide[3] might also be helpful (and only a fraction of the pages are relevant.)
0. https://github.com/tinygrad/tinygrad/blob/master/extra/gemm/...
1. https://gpuopen.com/learn/wmma_on_rdna3/
2. https://github.com/ROCm/HIPCC
3. https://www.amd.com/content/dam/amd/en/documents/radeon-tech...
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Beyond Backpropagation - Higher Order, Forward and Reverse-mode Automatic Differentiation for Tensorken
This post describes how I added automatic differentiation to Tensorken. Tensorken is my attempt to build a fully featured yet easy-to-understand and hackable implementation of a deep learning library in Rust. It takes inspiration from the likes of PyTorch, Tinygrad, and JAX.
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[D] What is a good way to maintain code readability and code quality while scaling up complexity in libraries like Hugging Face?
what do you think about tinygrad? I think its a good example of growing and well written, (partially) well documented library with many close to reference implementations
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💻 7 Open-Source DevTools That Save Time You Didn't Know to Exist ⌛🚀
🌟 Support on GitHub Website: https://tinygrad.org/
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Decomposing Language Models into Understandable Components
Try to get something like tinygrad[1] running locally, that way you can tweak things a bit run it again and see how it performs. While doing this you'll pick up most of the concepts and get a feeling of how things work. Also, take a look at projects like llama.cpp[2], you don't have to fully understand what's going on here, tho.
You may need some intermediate knowledge of linear algebra and this thing called "data science" nowadays, which is pretty much knowing how to mangle data and visualize it.
Try creating a small model on your own, it doesn't have to be super fancy just make sure it does something you want it to do. And then ... you'll probably could go on your own then.
- Stable Diffusion in pure C/C++
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There is no hard takeoff
lol, you should see me bash my own code. I'm even more mean.
https://github.com/tinygrad/tinygrad/blob/master/examples/hl...
have a bunch of bounties on it, we're getting 94%+ now! mostly not me who wrote this, see history. have to switch to float16 and add Winograd convs still. we have a branch with multigpu too.
goal is to beat an A100 in speed on a tinybox.
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MatX: Faster Chips for LLMs
AMD drivers are a higher priority but he also made tinygrad https://github.com/tinygrad/tinygrad
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[Project] Whisper Implementation in Rust using burn
I temporarily switched from Rust to Python for machine learning, but quickly became fed up with Python's annoying versioning issues and runtime errors. I looked for a better path to machine learning and discovered burn, a deep learning framework for Rust. As my first burn project I decided to port OpenAI's Whisper transcription model. The project can be found at Gadersd/whisper-burn: A Rust implementation of OpenAI's Whisper model using the burn framework (github.com). I based it on the excellently concise tinygrad implementation that can be found here. The tinygrad version begrudgingly uses Torch's stft which I ported into a pure Rust short time Fourier transform along with the mel scale frequency conversion matrix function because I am curious and just a bit masochistic.
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Onnx Runtime: “Cross-Platform Accelerated Machine Learning”
Be better to use https://github.com/tinygrad/tinygrad as an intermediary framework?
mac-precision-touchpad
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Why Android developers no longer need Windows USB drivers
Link for reference:
> Bingxing Wang's awesome [Windows Precision Touchpad Implementation for Apple MacBook family/Magic Trackpad 2] driver[0].
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My first build, wireless mx corne.
Can confirm. Works perfectly. Drivers are on github.
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are there any tools/softwares that slightly improve how well windows works on a bootcamped Mac?
But no, if you install it without Chocolatey, you don't need other software. Download it from the release page here, unzip it, right-click on AmtPtpDevice.inf, and choose the install option from the context menu. If you're using Windows 11 you might have to click 'More Options' or whatever when you right-click, as it hides basically everything.
I always install the Precision Touchpad Driver. This might depend on the age of your machine, though. I think Boot Camp drivers for the last Intel generation include this by default. (But I don't know that for certain. I do know that 2012 Macbook Pro sure doesn't.)
- "Macs make better Windows machines than most Windows machines."
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This laptop has a trackpad above the keyboard
Not officially supported, but yeah, they do work on windows
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I Use My Mouse
I love my CST L-Trac but sometimes I wish I'd gotten the version with the extra button inputs to setup some extra keybinds.
Alternatively I've finally become used to having a magictrackpad2 and gestures. And thank you other devs[1] for someone getting it working on Windows x86/ARM64 builds as well. Next step is trying to find out if I can get it working fully under FreeBSD.
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Things I've learned enabling bootcamp in my MacBookAir 2017
Touchpad feels like 20 years ago laptop: Just install the open source precision touchpad driver.
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Are there any trackpads for Windows with full multi-touch gesture support?
This driver on Github turns the magic trackpad 2 into a precision touchpad for windows to understand and configure.
What are some alternatives?
Pytorch - Tensors and Dynamic neural networks in Python with strong GPU acceleration
barrier - Open-source KVM software
jax - Composable transformations of Python+NumPy programs: differentiate, vectorize, JIT to GPU/TPU, and more
llama.cpp - LLM inference in C/C++
winget-cli - WinGet is the Windows Package Manager. This project includes a CLI (Command Line Interface), PowerShell modules, and a COM (Component Object Model) API (Application Programming Interface).
qmk_firmware - Open-source keyboard firmware for Atmel AVR and Arm USB families
veikk-linux-driver - Linux driver for VEIKK-brand digitizers
brigadier - Fetch and install Boot Camp ESDs with ease.
brigadier - Brigadier is a command parser & dispatcher, designed and developed for Minecraft: Java Edition.
Windows-screenFetch - Powershell port of bash/unix screenfetch.
llama - Inference code for Llama models
PowerToys - Windows system utilities to maximize productivity