TransformerEngine
Pytorch
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TransformerEngine | Pytorch | |
---|---|---|
2 | 338 | |
1,428 | 77,783 | |
13.1% | 2.4% | |
9.5 | 10.0 | |
4 days ago | 6 days ago | |
Python | Python | |
Apache License 2.0 | BSD 1-Clause 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.
TransformerEngine
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Benchmarking Large Language Models on NVIDIA H100 GPUs with CoreWeave (Part 1)
4090 now has its 8-bit float enabled as well, see the [transformer engine issue](https://github.com/NVIDIA/TransformerEngine/issues/15)
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GPUs for Deep Learning in 2023 – An In-depth Analysis
Would be curious to see your benchmarks. Btw, Nvidia will be providing support for fp8 in a future release of CUDA - https://github.com/NVIDIA/TransformerEngine/issues/15
I think TMA may not matter as much for consumer cards given the disproportionate amount of fp32 / int32 compute that they have.
Would be interesting to see how close to theoretical folks are able to get once CUDA support comes through.
Pytorch
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Einsum in 40 Lines of Python
PyTorch also has some support for them, but it's quite incomplete and has many issues so that it is basically unusable. And its future development is also unclear. https://github.com/pytorch/pytorch/issues/60832
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Library for Machine learning and quantum computing
TensorFlow
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My Favorite DevTools to Build AI/ML Applications!
TensorFlow, developed by Google, and PyTorch, developed by Facebook, are two of the most popular frameworks for building and training complex machine learning models. TensorFlow is known for its flexibility and robust scalability, making it suitable for both research prototypes and production deployments. PyTorch is praised for its ease of use, simplicity, and dynamic computational graph that allows for more intuitive coding of complex AI models. Both frameworks support a wide range of AI models, from simple linear regression to complex deep neural networks.
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penzai: JAX research toolkit for building, editing, and visualizing neural nets
> does PyTorch have a similar concept
of course https://github.com/pytorch/pytorch/blob/main/torch/utils/_py...
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Tinygrad: Hacked 4090 driver to enable P2P
fyi should work on most 40xx[1]
[1] https://github.com/pytorch/pytorch/issues/119638#issuecommen...
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The Elements of Differentiable Programming
Sure, right here: https://github.com/pytorch/pytorch/blob/main/torch/autograd/...
Here's the documentation: https://pytorch.org/tutorials/intermediate/forward_ad_usage....
> When an input, which we call “primal”, is associated with a “direction” tensor, which we call “tangent”, the resultant new tensor object is called a “dual tensor” for its connection to dual numbers[0].
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Functions and operators for Dot and Matrix multiplication and Element-wise calculation in PyTorch
*My post explains Dot, Matrix and Element-wise multiplication in PyTorch.
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Dot vs Matrix vs Element-wise multiplication in PyTorch
In PyTorch with @, dot() or matmul():
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Building a GPT Model from the Ground Up!
import torch # we use PyTorch: https://pytorch.org data = torch.tensor(encode(text), dtype=torch.long) print(data.shape, data.dtype) print(data[:1000]) # the 1000 characters we looked at earlier will to the GPT look like this
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Open Source Ascendant: The Transformation of Software Development in 2024
AI's Open Embrace Artificial intelligence (AI) and machine learning (ML) are increasingly leveraging open-source frameworks like TensorFlow [https://www.tensorflow.org/] and PyTorch [https://pytorch.org/]. This democratization of AI tools is driving innovation and lowering entry barriers across industries.
What are some alternatives?
Whisper - High-performance GPGPU inference of OpenAI's Whisper automatic speech recognition (ASR) model
Flux.jl - Relax! Flux is the ML library that doesn't make you tensor
autocvd - Tool to automatically set CUDA_VISIBLE_DEVICES based on GPU utilization. Usable from command line and code.
mediapipe - Cross-platform, customizable ML solutions for live and streaming media.
warp-drive - Extremely Fast End-to-End Deep Multi-Agent Reinforcement Learning Framework on a GPU (JMLR 2022)
Apache Spark - Apache Spark - A unified analytics engine for large-scale data processing
ivy - The Unified AI Framework
flax - Flax is a neural network library for JAX that is designed for flexibility.
nanoGPT - The simplest, fastest repository for training/finetuning medium-sized GPTs.
tinygrad - You like pytorch? You like micrograd? You love tinygrad! ❤️ [Moved to: https://github.com/tinygrad/tinygrad]
fastaudio - 🔊 Audio and fastai v2
Pandas - Flexible and powerful data analysis / manipulation library for Python, providing labeled data structures similar to R data.frame objects, statistical functions, and much more