Shared Ultralytics logos, media, sample images, pretrained model weights, dataset artifacts, and release assets.
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Updated
Sep 14, 2026
Shared Ultralytics logos, media, sample images, pretrained model weights, dataset artifacts, and release assets.
Training with FP16 weights in PyTorch
The high-performance distributed tensor layer — load once, share everywhere.
🎓 2020 Undergraduate Graduation Project in Jiangnan University ALL codes including Data-convert, keras-Train, model-Evaluate and Web-App
Verified multi-source distribution for local LLM weights
ClimWIP allows to calculate & apply performance and independence weights to CMIP models
Utility tool for Intel(r) OpenVINO(tm) IR models. The tool can display detailed model information, layer information and can check compatibility. The tool also can extract weight data and feature map from the IR model.
Pre-compiled ASR model weights for the VoxRT on-device runtime. Encrypted .vxrt v2 format. streaming-medium-pc: FastConformer 32M, CTC + RNN-T, CC-BY-4.0 (NVIDIA NeMo).
CrowdGPT is an opensource AI that aims to be trained without any datacenters
Flow-driven recursive skill evolution for agentic LLM orchestration.
Wake-phrase model weights (.vxrt, ~100 KB, AES-GCM encrypted) for the VoxRT custom on-device inference runtime. Paired with voxrt-wake-word-{android,ios,linux}. Custom phrases at voxrt.com.
14-way keyword-spotting model weights (.vxrt v2, AES-256-GCM encrypted) for the VoxRT on-device runtime. Streaming Conformer-Medium (636 K params, 1.28 MB). Paired with voxrt-kws-{linux,browser}.
The Brain Collector: Find ML model weights inside Android
Independent Safetensors format implementation for Mojo
Quantization Aware Training
Computer Vision Basics to advanced. My journey through this subfield of AI
This GitHub repository provides an implementation of a Genetic Algorithm (GA) for finding optimal weights of a Neural Network (NN).
PXG-Tiny Ai - pixel sprites game asset generator. A 483K-param open-weights model that turns plain English prompts into 16×16 pixel-art sprites — ~1 MB NumPy weights, CPU-only, fully offline.
Template for Cog models with built-in model weights caching and CDN integration
tensorsentry
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