dmarx/dmarx-github-stars huggingface dataset:
Repository: tysam-code/hlb-CIFAR10
Description: Train to 94% on CIFAR-10 in <6.3 seconds on a single A100, the current world speed record. Or ~95.79% in ~110 seconds (or less!)
Language: Python
Topics: cifar10, deep-learning, experimentation, language-models-are-next, machine-learning, neural-network, responsive-to-issue-tickets, speedyconvnet7-1-0, world-record
Homepage: https://twitter.com/hi_tysam
Repository: intel/neural-compressor
Description: SOTA low-bit LLM quantization (INT8/FP8/INT4/FP4/NF4) & sparsity; leading model compression techniques on TensorFlow, PyTorch, and ONNX Runtime
Language: Python
Topics: auto-tuning, awq, fp4, gptq, int4, int8, knowledge-distillation, large-language-models, low-precision, mxformat, post-training-quantization, pruning, quantization, quantization-aware-training, smoothquant, sparsegpt, sparsity
Homepage: https://intel.github.io/neural-compressor/
Repository: run-house/runhouse
Description: The fastest way to deploy AI apps and services on any infra. Unobtrusive, debuggable, PyTorch-like APIs.
Language: Python
Topics: api, artificial-intelligence, aws, azure, collaboration, data-science, deployment, distributed, fastapi, gcp, infrastructure, machine-learning, middleware, observability, python, pytorch, ray, sagemaker, serverless
Homepage: https://run.house