heatdrop.ai

A model-agnostic Python toolkit that handles the boring parts of computer vision: annotations, dataset juggling, and tracking.

A PyTorch implementation of "Attention Is All You Need" that scales from 13M to multi-billion parameter models.

OpenMed packages clinical entity extraction and HIPAA-grade de-identification into models small enough for Apple Silicon and impatient DevOps teams.

Companion notebooks for an 800-page quantitative finance textbook, from linear regression to deep reinforcement learning trading agents.

A notebook-based workout plan for PyTorch fluency, from linear regression up to building LLM components from scratch.

Reproducible world-model research is usually a pile of glue scripts; this library tries to make it a single import.

A C-based RL library claiming to train super-human models in seconds, built from scratch by a research team that also sells professional environments.

MLX-VLM crams speculative decoding, continuous batching, and KV cache quantization into a Mac-native toolkit for running multimodal models locally.

Chinese open-source community Datawhale built a from-zero embodied-AI course that gets you from `print('hello')` to fine-tuning SmolVLA and Pi0.

A grab-bag node pack whose Set/Get rewrite might finally tame your worst workflow tangles.

A single Python framework that pretrains DINOv2/v3 on unlabeled data, then fine-tunes and distills for detection and segmentation tasks.

A curated, Qualcomm-optimized model catalog that handles the messy translation from PyTorch to on-device NPU binaries.

A Python bridge that turns messy geospatial data—streets, transit feeds, building footprints—into PyTorch Geometric tensors without the usual hand-rolled pain.

Curated technical deep-dives covering everything from NVLink signal integrity to Kubernetes GPU scheduling and Huawei NPU porting.

A world-model RL algorithm that reportedly needs no tuning across Atari, Minecraft, and continuous control.

Pre-trained voice activity detection that runs on a CPU thread in under a millisecond, no API keys or telemetry attached.

Megatron-LM splits into a reference training stack and a composable core for anyone who needs to squeeze every FLOP from a GPU cluster.

TransformerLens lets you intercept, cache, and surgically edit the hidden activations of 50+ language models as they run.

A pedagogical autograd engine so small you can read it on your coffee break, yet complete enough to train a real MLP.

ManiSkill 3 is a GPU-parallelized robotics framework built on SAPIEN that turns a single RTX 4090 into a data factory pumping out visual training data at 30,000+ FPS.