-
Preferred Networks
- Japan
-
15:33
(UTC +09:00) - https://akawashiro.com/
- @a_kawashiro
- @a_kawashiro@mstdn.jp
- in/akirakawata
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The simplest, fastest repository for training/finetuning medium-sized GPTs.
Pax is a Jax-based machine learning framework for training large scale models. Pax allows for advanced and fully configurable experimentation and parallelization, and has demonstrated industry lead…
Efficient Triton Kernels for LLM Training
Let's build a symbolic model checker from scratch in Rust !
The repository provides code for running inference with the Meta Segment Anything Model 2 (SAM 2), links for downloading the trained model checkpoints, and example notebooks that show how to use th…
PyTorch extension for emulating FP8 data formats on standard FP32 Xeon/GPU hardware.
Ohayou(おはよう), HTTP load generator, inspired by rakyll/hey with tui animation.
Tensors and Dynamic neural networks in Python with strong GPU acceleration
Nuitka is a Python compiler written in Python. It's fully compatible with Python 2.6, 2.7, 3.4-3.12. You feed it your Python app, it does a lot of clever things, and spits out an executable or exte…
maekawatoshiki / pykan
Forked from KindXiaoming/pykanKolmogorov Arnold Networks
ONNX Runtime: cross-platform, high performance ML inferencing and training accelerator
Enhancements tracking repo for Kubernetes
Garnet is a remote cache-store from Microsoft Research that offers strong performance (throughput and latency), scalability, storage, recovery, cluster sharding, key migration, and replication feat…
Must read research papers and links to tools and datasets that are related to using machine learning for compilers and systems optimisation
A list of awesome compiler projects and papers for tensor computation and deep learning.
Tenstorrent console based hardware information program
A garbage collection library for Rust with zero unsafe code
A unikernel designed specifically for running Wasm applications and compatible with WASI