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Contents

Large Language Model Papers·2021

Codex: Evaluating Large Language Models Trained on Code

Mark Chen, Jerry Tworek +2·OpenAI

Showed that fine-tuning a GPT model on public GitHub code yields a capable program synthesizer, and introduced HumanEval — the docstring-to-function benchmark that still anchors code-generation evaluation. A production variant powers GitHub Copilot.

#openai#code#codex#copilot#evaluation+2
GitHub
MLOps·2021
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OpenMetadata

OpenMetadata

Unified metadata platform for data discovery, observability, and governance — central metadata repository, column-level lineage, and a pluggable ingestion framework with 84+ connectors. Suited for teams that need searchable data catalogs, automated lineage, and collaborative data governance.

#mlops#github#docker#postgres#ai-workflow+2
GitHub
AI Infra·2021
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SkyPilot

skypilot-org, Sky Computing Lab (UC Berkeley)·Sky Computing Lab, UC Berkeley

Runs, manages, and scales AI workloads across 20+ clouds, Kubernetes, Slurm, and on-prem from one YAML or Python spec. Auto-provisions GPUs/TPUs, fails over across regions and providers when capacity is short, and routes jobs to the cheapest option.

#mlops#ai-serving#ai-train#ai-workflow#ai-inference+2
GitHub
AI Client·2021
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khoj

Khoj AI (khoj-ai)

Self-hostable personal “AI second brain” that turns web pages and documents into a searchable knowledge base, builds custom agents and automations, and connects to local or cloud LLMs with multi-platform access.

#github#chatbot#llm#RAG#embeddings+3
AI Deploy·2021
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KServe

KServe community·Google, IBM +4

Serves predictive and generative ML models on Kubernetes via a single InferenceService CRD, with scale-to-zero, canary rollouts, and an OpenAI-compatible LLM path on vLLM. One autoscaling abstraction over PyTorch, XGBoost, ONNX, and HuggingFace.

#mlops#ai-inference#ai-serving#ai-deploy#vllm+3
GitHub
AI Infra·2021
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xFormers

Facebook Research (Meta)·Meta AI

Drop-in transformer building blocks with custom CUDA kernels: memory-efficient exact attention (up to ~10x faster), block-sparse attention, fused softmax/layernorm/SwiGLU ops. Cuts VRAM and speeds up diffusion and LLM training on Nvidia GPUs.

#pytorch#ai-library#meta-ai#ai-development#foundation-model+1
GitHub
AI Others·2021
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CS 自学指南

PKUFlyingPig

Curated self-study roadmap and reading-list for learning computer science end-to-end — organizes open courses, textbooks, and project recommendations across programming languages, systems, algorithms, AI/ML and more; aimed at motivated learners planning a 2–3 year self-directed path.

#book#course#algorithms#python#java+4
AI Train·2021
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Colossal-AI

HPC-AI Technology Inc. (Colossal-AI team), Shenggui Li +1·HPC-AI Technology Inc., National University of Singapore

Scales a single-GPU training script to thousands of GPUs through a unified interface, combining data, pipeline, tensor, and sequence parallelism. Its Gemini memory manager offloads tensors across GPU, CPU, and NVMe so models far larger than VRAM still fit.

#pytorch#ai-train#ai-inference#ai-serving#mlops+3
GitHub
AI Image·2021
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Anomalib

open-edge-platform

Library for benchmarking, developing, and deploying deep-learning visual anomaly-detection models — includes ready-to-use model implementations (PatchCore, DINO-based), experiment/HPO tooling, OpenVINO export for edge inference, and a low-code Studio for deployment.

#vision#pytorch#ai-inference#ai-serving#ai-library+3
MLOps·2021
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ZenML — The AI Control Plane

Adam Probst, Hamza Tahir +1·ZenML GmbH

Orchestrates ML training pipelines and production agent workflows from one Python codebase that runs unchanged from a laptop to Kubernetes or any cloud. Auto-versions artifacts, models, and agent checkpoints, with no orchestrator or framework lock-in.

#mlops#ai-workflow#ai-development#ai-tools#python+5
GitHub
AI Infra·2022
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Self Hosting Guide

mikeroyal

A continuously-updated, categorized self-hosting guide that catalogs tools, deployment notes and resources for containers, networking, home automation and running LLMs/chatbots locally; provided as a long, structured README with links and quick setup tips.

#docker#llm#privacy#pi#chatbot+2
GitHub
AI Deploy·2022
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ExecuTorch

PyTorch·Meta

Deploys PyTorch models directly on phones, microcontrollers, and embedded hardware via ahead-of-time compilation to a ~50KB C++ runtime. Delegates subgraphs to 12+ backends (XNNPACK, CoreML, Qualcomm, ARM Ethos-U) with torchao quantization.

#pytorch#ai-inference#ai-serving#meta-ai#llm+5
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