Winning Health Optimizes LLMs in Healthcare
…With Intel® Extension for PyTorch, Intel uses acceleration libraries such as oneDNN and oneCCL in the form of intel-extension-for-pytorch as a plug-in to improve PyTorch performance on servers…
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PyTorch
Videos
More videosFederated Learning Without the Refactoring Overhead Using NVIDIA FLARE | NVIDIA Technical Blog
…import, patch, (optional) validate, train as usual. # lightning_client.py import pytorch_lightning as pl from pytorch_lightning import Trainer import nvflare.client.lightning as flare # Lightning Client API from model import…
HippoScreen Neurotech
Ecosystem Developer Resources By "We at HippoScreen* have been able to take advantage of the software optimizations in Intel® Extension for Scikit-learn* and Intel® Extension for PyTorch* to accelerate the build…
AMD ROCm™ 7.2.1 on Radeon™ and Ryzen™ for Linux® Release Notes
…PyTorch, the PyTorch logo and any related marks are trademarks of The Linux Foundation.
Discussions and forums
Running PyTorch Models on Apple Silicon GPUs with the ExecuTorch MLX Delegate
Running PyTorch Models on Apple Silicon GPUs with the ExecuTorch MLX Delegate
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Running PyTorch Models on Apple Silicon GPUs with the ExecuTorch MLX Delegate
Running PyTorch Models on Apple Silicon GPUs with the ExecuTorch MLX Delegate
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Show HN: We built an LLM inference engine in pure Python – no PyTorch, no Triton
Show HN: We built an LLM inference engine in pure Python – no PyTorch, no Triton
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Show HN: I built a 2nd-order PyTorch optimizer for LLMs that runs on 16GB GPUs
Hi HN,I'm Danilo. I've been struggling with the limitations of AdamW when fine-tuning LLMs locally. Second-order optimizers (like Shampoo or SOAP) offer significantly better step-convergence by exploiting Kronecker-facto…
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Show HN: Run TRELLIS.2 Image-to-3D generation natively on Apple Silicon
I ported Microsoft's TRELLIS.2 (4B parameter image-to-3D model) to run on Apple Silicon via PyTorch MPS. The original requires CUDA with flash_attn, nvdiffrast, and custom sparse convolution kernels: none of which work …
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AMD Developer Central
…Tools AMD is committed to open-source innovation, contributing to projects like the Linux Kernel, PyTorch, Hugging Face, and TensorFlow. To support developers, AMD also offers open-source tools to help analyze…
ZenDNN 5.2: Accelerating vLLM V1 Engine and Recommender Systems Inference on AMD EPYC™ CPUs
…Modernized Stack : Full support for TensorFlow 2.20 , PyTorch 2.10.0 , and Python 3.13. ZenDNN Backend for Llama.cpp : Engineered during the 5.2 development cycle, this integration allows Llama…
Launching AMD AI Playbooks: Step-by-Step Guides for Building with AI Locally with AMD
…Run a local coding assistant on-device LM Studio - Serve and interact with local LLMs PyTorch + ROCm™ software - Run and accelerate LLM workloads, including tasks like summarization More playbooks will continue to…
AMD Ryzen™ AI Software
AMD Ryzen™ AI Software Tools and runtime libraries for optimizing and deploying AI inference on AI PCs Overview Ryzen™ AI software enables developers to efficiently port their pre-trained PyTorch or TensorFlow…
LLM Inference on Edge: A Fun and Easy Guide to run LLMs via React Native on your Phone!
…Maybe integration from pytorch into tensorflow to take advantage of the M chip in Pixel to really make this stuff scream, using a tool like google-ai-edge/ai-edge-torch. Great…
H100 vs GB200 NVL72 Training Benchmarks - Power, TCO, and Reliability Analysis, Software Improvement Over Time
…To this end, more Nvidia engineers should be allocated towards PyTorch core development instead of being tasked with adding more features to NeMo. Nvidia expanding benchmarking focus should include runs employing PyTorch…