GPT-J inference on the CPU using C/C++
Tensor library for machine learning. Contribute to ggml-org/ggml development by creating an account on GitHub.
GPT-J inference on the CPU using C/C++ launched on September 20, 2022 with 5 votes, #1,231 of 3,464 launches that month and more than 50% of that year's launches. The site was still online in September 2026, 4 years on.
Does a similar job
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Comprehensive Tutorials in Deep Learning Using TensorFlow2018 · github.com · ▲327:satellite: Simple and ready-to-use tutorials for TensorFlow - GitHub - instillai/TensorFlow-Course: :satellite: Simple and ready-to-use tutorials for TensorFlow
I built a tensor library from scratch in C++/CUDA2025 · github.com · ▲119Hi HN, Over the past few months, I've been building `dsc`, a tensor library from scratch in C++/CUDA. My main focus has been on getting the basics right, prioritizing a clean API, simplicity, and clear observability for running small LLMs locally. The key features are: - C++ core with CUDA support written from scratch. - A familiar, PyTorch-like Python API. - Runs real models: it's complete enough to load a model like Qwen from HuggingFace and run inference on both CUDA and CPU with a single line change[1]. - Simple, built-in observability for both Python and C++. Next on the roadmap is…
less than 650 LOC trainable GPT only using NumPy2023 · github.com · ▲90Absolute minimalistic implementation of a GPT-like transformer using only numpy (<650 lines). - joennlae/tensorli
GPT-2 implemented using graphics shaders2025 · github.com · ▲228Back in the old days, people used to do general-purpose GPU programming by using shaders like GLSL. This is what inspired NVIDIA (and other companies) to eventually create CUDA (and friends). This is an implementation of GPT-2 using WebGL and shaders. Enjoy!
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Source: Show HN post ↗
Launched alongside, September 2022
the whole month →- IM
Life & fun · 2022 · dogbunnypuzzle.com
A couple of years ago, I had an interesting idea. What if there was a marketplace where all the underlying tech was open-source? The order management system, the storefront, customer support, etc. The marketplace would simply connect to the seller’s infra instead of locking them in. If, for some reason, the seller is removed from the marketplace, their software stays with them and they can continue accepting orders directly. This model can be used to disrupt any marketplace from AirBNB to UberEats: building tech for home renters and restaurants and later, leveraging that to build a competing…
Dev tools · 2022 · openship.org
