jittor
tinygrad
| jittor | tinygrad | |
|---|---|---|
| 4 | 58 | |
| 3,016 | 17,800 | |
| - | - | |
| 8.1 | 9.7 | |
| 6 days ago | 11 months ago | |
| Python | Python | |
| Apache License 2.0 | 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.
jittor
-
VSL; Vlang's Scientific Library
Would it make sense to have a backend support for OpenXLA, Apache TVM, Jittor or other similar to get free GPU, TPU and other accelerators for free ?
- Jittor: High-performance deep learning framework based on JIT and meta-operators
-
Tinygrad: A simple and powerful neural network framework
Very similar idea as Jittor, convolution definitely can be break down: https://github.com/Jittor/jittor/blob/master/python/jittor/n...
-
How do I deal with ML models taking soooo long to train, when I have to optimize results?
-I've found JIT quite useful: https://github.com/Jittor/jittor
tinygrad
- tinygrad: extreme simplicity, easiest framework to add new accelerators to
-
GGML – AI at the Edge
Might be a silly question but is GGML a similar/competing library to George Hotz's tinygrad [0]?
[0] https://github.com/geohot/tinygrad
-
Render neural network into CUDA/HIP code
at first glance i thought may its like tinygrad. but looks has many ops than that tiny grad but most maps to underlying hardware provided ops?
i wonder how well tinygrad's apporach will work out, ops fusion sounds easy, just a walk a graph, pattern match it and lower to hardware provided ops?
Anyway if anyone wants to understand the philosophy behind tinygrad, this file is great start https://github.com/geohot/tinygrad/blob/master/docs/abstract...
-
llama.cpp now officially supports GPU acceleration.
There are currently at least 3 ways to run llama on m1 with GPU acceleration. - mlc-llm (pre-built, only 1 model has been ported) - tinygrad (very memory efficient, not that easy to integrate into other projects) - llama-mps (original llama codebase + llama adapter support)
- George Hotz building an AMD competitor to Nvidia.
-
George Hotz ROCm adventures
Hopefully we will see now full support with AMD hardware on https://github.com/geohot/tinygrad. You can read more about it on https://tinygrad.org/
-
The Coming of Local LLMs
tinygrad
https://github.com/geohot/tinygrad/tree/master/accel/ane
But I have not tested it on Linux since Asahi has not yet added support.
llama.cpp runs at 18ms per token (7B) and 200ms per token (65B) without quantization.
- Everything we know about Apple's Neural Engine
- Everything we know about the Apple Neural Engine (ANE)
- How 'Open' Is OpenAI, Really?
What are some alternatives?
Res2Net-PretrainedModels - (ImageNet pretrained models) The official pytorch implemention of the TPAMI paper "Res2Net: A New Multi-scale Backbone Architecture"
Pytorch - Tensors and Dynamic neural networks in Python with strong GPU acceleration
shumai - Fast Differentiable Tensor Library in JavaScript and TypeScript with Bun + Flashlight
llama.cpp - LLM inference in C/C++
tvm - Open deep learning compiler stack for cpu, gpu and specialized accelerators
openpilot - openpilot is an open source driver assistance system. openpilot performs the functions of Automated Lane Centering and Adaptive Cruise Control for 250+ supported car makes and models.
vsl - V library to develop Artificial Intelligence and High-Performance Scientific Computations
llama - Inference code for Llama models
StylizedNeRF - [CVPR 2022] Code for StylizedNeRF: Consistent 3D Scene Stylization as Stylized NeRF via 2D-3D mutual learning
tensorflow_macos - TensorFlow for macOS 11.0+ accelerated using Apple's ML Compute framework.
nnabla - Neural Network Libraries
GPTQ-for-LLaMa - 4 bits quantization of LLaMA using GPTQ