Added unique contributors count

PyTorchConference2025_GithubRepos.json

@@ -5,13 +5,21 @@
     "category": "agent",
     "github_about_section": "an open source, extensible AI agent that goes beyond code suggestions - install, execute, edit, and test with any LLM",
     "homepage_link": "https://block.github.io/goose",
-    "github_topic_closest_fit": "ai-agents"
+    "github_topic_closest_fit": "ai-agents",
+    "contributors_all": "332",
+    "contributors_2025": "319",
+    "contributors_2024": "32",
+    "contributors_2023": "0"
   },
   {
     "repo_name": "ray",
     "repo_link": "https://github.com/ray-project/ray",
     "github_about_section": "Ray is an AI compute engine. Ray consists of a core distributed runtime and a set of AI Libraries for accelerating ML workloads.",
-    "homepage_link": "https://ray.io"
+    "homepage_link": "https://ray.io",
+    "contributors_all": "1381",
+    "contributors_2025": "397",
+    "contributors_2024": "223",
+    "contributors_2023": "230"
   },
   {
     "repo_name": "flashinfer-bench",
@@ -19,7 +27,11 @@
     "category": "benchmark",
     "github_about_section": "Building the Virtuous Cycle for AI-driven LLM Systems",
     "homepage_link": "https://bench.flashinfer.ai",
-    "github_topic_closest_fit": "benchmark"
+    "github_topic_closest_fit": "benchmark",
+    "contributors_all": "12",
+    "contributors_2025": "11",
+    "contributors_2024": "0",
+    "contributors_2023": "0"
   },
   {
     "repo_name": "KernelBench",
@@ -27,7 +39,11 @@
     "category": "benchmark",
     "github_about_section": "KernelBench: Can LLMs Write GPU Kernels? - Benchmark with Torch -> CUDA problems",
     "homepage_link": "https://scalingintelligence.stanford.edu/blogs/kernelbench",
-    "github_topic_closest_fit": "benchmark"
+    "github_topic_closest_fit": "benchmark",
+    "contributors_all": "19",
+    "contributors_2025": "16",
+    "contributors_2024": "3",
+    "contributors_2023": "0"
   },
   {
     "repo_name": "SWE-bench",
@@ -35,7 +51,11 @@
     "category": "benchmark",
     "github_about_section": "SWE-bench: Can Language Models Resolve Real-world Github Issues?",
     "homepage_link": "https://swebench.com",
-    "github_topic_closest_fit": "benchmark"
+    "github_topic_closest_fit": "benchmark",
+    "contributors_all": "66",
+    "contributors_2025": "33",
+    "contributors_2024": "37",
+    "contributors_2023": "9"
   },
   {
     "repo_name": "terminal-bench",
@@ -43,7 +63,11 @@
     "category": "benchmark",
     "github_about_section": "A benchmark for LLMs on complicated tasks in the terminal",
     "homepage_link": "https://tbench.ai",
-    "github_topic_closest_fit": "benchmark"
+    "github_topic_closest_fit": "benchmark",
+    "contributors_all": "96",
+    "contributors_2025": "96",
+    "contributors_2024": "0",
+    "contributors_2023": "0"
   },
   {
     "repo_name": "TritonBench",
@@ -51,21 +75,33 @@
     "category": "benchmark",
     "github_about_section": "TritonBench: Benchmarking Large Language Model Capabilities for Generating Triton Operators",
     "homepage_link": "https://arxiv.org/abs/2502.14752",
-    "github_topic_closest_fit": "benchmark"
+    "github_topic_closest_fit": "benchmark",
+    "contributors_all": "3",
+    "contributors_2025": "3",
+    "contributors_2024": "0",
+    "contributors_2023": "0"
   },
   {
     "repo_name": "BitBLAS",
     "repo_link": "https://github.com/microsoft/BitBLAS",
     "category": "Basic Linear Algebra Subprograms (BLAS)",
     "github_about_section": "BitBLAS is a library to support mixed-precision matrix multiplications, especially for quantized LLM deployment.",
-    "github_topic_closest_fit": "matrix-multiplication"
+    "github_topic_closest_fit": "matrix-multiplication",
+    "contributors_all": "17",
+    "contributors_2025": "5",
+    "contributors_2024": "14",
+    "contributors_2023": "0"
   },
   {
     "repo_name": "hipBLAS",
     "repo_link": "https://github.com/ROCm/hipBLAS",
     "category": "Basic Linear Algebra Subprograms (BLAS)",
     "github_about_section": "[DEPRECATED] Moved to ROCm/rocm-libraries repo",
-    "github_topic_closest_fit": "matrix-multiplication"
+    "github_topic_closest_fit": "matrix-multiplication",
+    "contributors_all": "72",
+    "contributors_2025": "21",
+    "contributors_2024": "24",
+    "contributors_2023": "14"
   },
   {
     "repo_name": "hipBLASLt",
@@ -73,13 +109,21 @@
     "category": "Basic Linear Algebra Subprograms (BLAS)",
     "github_about_section": "hipBLASLt is a library that provides general matrix-matrix operations with a flexible API and extends functionalities beyond a traditional BLAS library",
     "homepage_link": "https://rocm.docs.amd.com/projects/hipBLASLt",
-    "github_topic_closest_fit": "matrix-multiplication"
+    "github_topic_closest_fit": "matrix-multiplication",
+    "contributors_all": "111",
+    "contributors_2025": "69",
+    "contributors_2024": "70",
+    "contributors_2023": "35"
   },
   {
     "repo_name": "AdaptiveCpp",
     "repo_link": "https://github.com/AdaptiveCpp/AdaptiveCpp",
     "github_about_section": "Compiler for multiple programming models (SYCL, C++ standard parallelism, HIP/CUDA) for CPUs and GPUs from all vendors: The independent, community-driven compiler for C++-based heterogeneous programming models. Lets applications adapt themselves to all the hardware in the system - even at runtime!",
-    "homepage_link": "https://adaptivecpp.github.io"
+    "homepage_link": "https://adaptivecpp.github.io",
+    "contributors_all": "93",
+    "contributors_2025": "32",
+    "contributors_2024": "32",
+    "contributors_2023": "24"
   },
   {
     "repo_name": "llvm-project",
@@ -87,68 +131,108 @@
     "category": "compiler",
     "github_about_section": "The LLVM Project is a collection of modular and reusable compiler and toolchain technologies.",
     "homepage_link": "http://llvm.org",
-    "github_topic_closest_fit": "compiler"
+    "github_topic_closest_fit": "compiler",
+    "contributors_all": "6680",
+    "contributors_2025": "2378",
+    "contributors_2024": "2130",
+    "contributors_2023": "1920"
   },
   {
     "repo_name": "numba",
     "repo_link": "https://github.com/numba/numba",
     "github_about_section": "NumPy aware dynamic Python compiler using LLVM",
-    "homepage_link": "https://numba.pydata.org"
+    "homepage_link": "https://numba.pydata.org",
+    "contributors_all": "430",
+    "contributors_2025": "36",
+    "contributors_2024": "32",
+    "contributors_2023": "55"
   },
   {
     "repo_name": "nvcc4jupyter",
     "repo_link": "https://github.com/andreinechaev/nvcc4jupyter",
     "github_about_section": "A plugin for Jupyter Notebook to run CUDA C/C++ code",
-    "homepage_link": "https://nvcc4jupyter.readthedocs.io"
+    "homepage_link": "https://nvcc4jupyter.readthedocs.io",
+    "contributors_all": "9",
+    "contributors_2025": "0",
+    "contributors_2024": "3",
+    "contributors_2023": "3"
   },
   {
     "repo_name": "CU2CL",
     "repo_link": "https://github.com/vtsynergy/CU2CL",
     "github_about_section": "A prototype CUDA-to-OpenCL source-to-source translator, built on the Clang compiler framework",
     "homepage_link": "http://chrec.cs.vt.edu/cu2cl",
-    "github_topic_closest_fit": "parallel-programming"
+    "github_topic_closest_fit": "parallel-programming",
+    "contributors_all": "3",
+    "contributors_2025": "0",
+    "contributors_2024": "0",
+    "contributors_2023": "0"
   },
   {
     "repo_name": "cuda-python",
     "repo_link": "https://github.com/NVIDIA/cuda-python",
     "github_about_section": "CUDA Python: Performance meets Productivity",
     "homepage_link": "https://nvidia.github.io/cuda-python",
-    "github_topic_closest_fit": "parallel-programming"
+    "github_topic_closest_fit": "parallel-programming",
+    "contributors_all": "48",
+    "contributors_2025": "41",
+    "contributors_2024": "12",
+    "contributors_2023": "1"
   },
   {
     "repo_name": "OpenCL-SDK",
     "repo_link": "https://github.com/KhronosGroup/OpenCL-SDK",
     "github_about_section": "OpenCL SDK",
     "homepage_link": "https://khronos.org/opencl",
-    "github_topic_closest_fit": "parallel-programming"
+    "github_topic_closest_fit": "parallel-programming",
+    "contributors_all": "25",
+    "contributors_2025": "8",
+    "contributors_2024": "6",
+    "contributors_2023": "9"
   },
   {
     "repo_name": "pocl",
     "repo_link": "https://github.com/pocl/pocl",
     "github_about_section": "pocl - Portable Computing Language",
     "homepage_link": "https://portablecl.org",
-    "github_topic_closest_fit": "parallel-programming"
+    "github_topic_closest_fit": "parallel-programming",
+    "contributors_all": "166",
+    "contributors_2025": "26",
+    "contributors_2024": "27",
+    "contributors_2023": "21"
   },
   {
     "repo_name": "SYCL-Docs",
     "repo_link": "https://github.com/KhronosGroup/SYCL-Docs",
     "github_about_section": "SYCL Open Source Specification",
     "homepage_link": "https://khronos.org/sycl",
-    "github_topic_closest_fit": "parallel-programming"
+    "github_topic_closest_fit": "parallel-programming",
+    "contributors_all": "67",
+    "contributors_2025": "13",
+    "contributors_2024": "20",
+    "contributors_2023": "27"
   },
   {
     "repo_name": "triSYCL",
     "repo_link": "https://github.com/triSYCL/triSYCL",
     "github_about_section": "Generic system-wide modern C++ for heterogeneous platforms with SYCL from Khronos Group",
     "homepage_link": "https://trisycl.github.io/triSYCL/Doxygen/triSYCL/html/index.html",
-    "github_topic_closest_fit": "parallel-programming"
+    "github_topic_closest_fit": "parallel-programming",
+    "contributors_all": "31",
+    "contributors_2025": "0",
+    "contributors_2024": "1",
+    "contributors_2023": "3"
   },
   {
     "repo_name": "ZLUDA",
     "repo_link": "https://github.com/vosen/ZLUDA",
     "github_about_section": "CUDA on non-NVIDIA GPUs",
     "homepage_link": "https://vosen.github.io/ZLUDA",
-    "github_topic_closest_fit": "parallel-programming"
+    "github_topic_closest_fit": "parallel-programming",
+    "contributors_all": "15",
+    "contributors_2025": "8",
+    "contributors_2024": "4",
+    "contributors_2023": "0"
   },
   {
     "repo_name": "llama.cpp",
@@ -156,7 +240,11 @@
     "category": "inference engine",
     "github_about_section": "LLM inference in C/C++",
     "homepage_link": "https://ggml.ai",
-    "github_topic_closest_fit": "inference"
+    "github_topic_closest_fit": "inference",
+    "contributors_all": "1374",
+    "contributors_2025": "535",
+    "contributors_2024": "575",
+    "contributors_2023": "461"
   },
   {
     "repo_name": "mistral-inference",
@@ -164,7 +252,11 @@
     "category": "inference engine",
     "github_about_section": "Official inference library for Mistral models",
     "homepage_link": "https://mistral.ai",
-    "github_topic_closest_fit": "inference"
+    "github_topic_closest_fit": "inference",
+    "contributors_all": "29",
+    "contributors_2025": "2",
+    "contributors_2024": "17",
+    "contributors_2023": "14"
   },
   {
     "repo_name": "ollama",
@@ -172,7 +264,11 @@
     "category": "inference engine",
     "github_about_section": "Get up and running with OpenAI gpt-oss, DeepSeek-R1, Gemma 3 and other models.",
     "homepage_link": "https://ollama.com",
-    "github_topic_closest_fit": "inference"
+    "github_topic_closest_fit": "inference",
+    "contributors_all": "574",
+    "contributors_2025": "202",
+    "contributors_2024": "314",
+    "contributors_2023": "97"
   },
   {
     "repo_name": "sglang",
@@ -180,13 +276,21 @@
     "category": "inference engine",
     "github_about_section": "SGLang is a fast serving framework for large language models and vision language models.",
     "homepage_link": "https://docs.sglang.ai",
-    "github_topic_closest_fit": "inference"
+    "github_topic_closest_fit": "inference",
+    "contributors_all": "937",
+    "contributors_2025": "796",
+    "contributors_2024": "189",
+    "contributors_2023": "1"
   },
   {
     "repo_name": "TensorRT",
     "repo_link": "https://github.com/NVIDIA/TensorRT",
     "github_about_section": "NVIDIA TensorRT is an SDK for high-performance deep learning inference on NVIDIA GPUs. This repository contains the open source components of TensorRT.",
-    "homepage_link": "https://developer.nvidia.com/tensorrt"
+    "homepage_link": "https://developer.nvidia.com/tensorrt",
+    "contributors_all": "104",
+    "contributors_2025": "10",
+    "contributors_2024": "18",
+    "contributors_2023": "19"
   },
   {
     "repo_name": "vllm",
@@ -194,20 +298,32 @@
     "category": "inference engine",
     "github_about_section": "A high-throughput and memory-efficient inference and serving engine for LLMs",
     "homepage_link": "https://docs.vllm.ai",
-    "github_topic_closest_fit": "inference"
+    "github_topic_closest_fit": "inference",
+    "contributors_all": "1885",
+    "contributors_2025": "1369",
+    "contributors_2024": "579",
+    "contributors_2023": "145"
   },
   {
     "repo_name": "kernels",
     "repo_link": "https://github.com/huggingface/kernels",
     "category": "gpu kernels",
-    "github_about_section": "Load compute kernels from the Hub"
+    "github_about_section": "Load compute kernels from the Hub",
+    "contributors_all": "15",
+    "contributors_2025": "14",
+    "contributors_2024": "2",
+    "contributors_2023": "0"
   },
   {
     "repo_name": "kernels-community",
     "repo_link": "https://github.com/huggingface/kernels-community",
     "category": "gpu kernels",
     "homepage_link": "https://huggingface.co/kernels-community",
-    "github_about_section": "Kernel sources for https://huggingface.co/kernels-community"
+    "github_about_section": "Kernel sources for https://huggingface.co/kernels-community",
+    "contributors_all": "9",
+    "contributors_2025": "9",
+    "contributors_2024": "0",
+    "contributors_2023": "0"
   },
   {
     "repo_name": "Liger-Kernel",
@@ -215,20 +331,32 @@
     "category": "kernel examples",
     "github_about_section": "Efficient Triton Kernels for LLM Training",
     "homepage_link": "https://openreview.net/pdf?id=36SjAIT42G",
-    "github_topic_closest_fit": "triton"
+    "github_topic_closest_fit": "triton",
+    "contributors_all": "120",
+    "contributors_2025": "78",
+    "contributors_2024": "61",
+    "contributors_2023": "0"
   },
   {
     "repo_name": "quack",
     "repo_link": "https://github.com/Dao-AILab/quack",
     "category": "kernel examples",
-    "github_about_section": "A Quirky Assortment of CuTe Kernels"
+    "github_about_section": "A Quirky Assortment of CuTe Kernels",
+    "contributors_all": "17",
+    "contributors_2025": "17",
+    "contributors_2024": "0",
+    "contributors_2023": "0"
   },
   {
     "repo_name": "reference-kernels",
     "repo_link": "https://github.com/gpu-mode/reference-kernels",
     "category": "kernel examples",
     "github_about_section": "Official Problem Sets / Reference Kernels for the GPU MODE Leaderboard!",
-    "homepage_link": "https://gpumode.com"
+    "homepage_link": "https://gpumode.com",
+    "contributors_all": "16",
+    "contributors_2025": "16",
+    "contributors_2024": "0",
+    "contributors_2023": "0"
   },
   {
     "repo_name": "pytorch",
@@ -236,7 +364,11 @@
     "category": "machine learning framework",
     "github_about_section": "Tensors and Dynamic neural networks in Python with strong GPU acceleration",
     "homepage_link": "https://pytorch.org",
-    "github_topic_closest_fit": "machine-learning"
+    "github_topic_closest_fit": "machine-learning",
+    "contributors_all": "5434",
+    "contributors_2025": "1187",
+    "contributors_2024": "1090",
+    "contributors_2023": "1024"
   },
   {
     "repo_name": "tensorflow",
@@ -244,13 +376,21 @@
     "category": "machine learning framework",
     "github_about_section": "An Open Source Machine Learning Framework for Everyone",
     "homepage_link": "https://tensorflow.org",
-    "github_topic_closest_fit": "machine-learning"
+    "github_topic_closest_fit": "machine-learning",
+    "contributors_all": "4618",
+    "contributors_2025": "500",
+    "contributors_2024": "523",
+    "contributors_2023": "630"
   },
   {
     "repo_name": "torchdendrite",
     "repo_link": "https://github.com/sandialabs/torchdendrite",
     "category": "machine learning framework",
-    "github_about_section": "Dendrites for PyTorch and SNNTorch neural networks"
+    "github_about_section": "Dendrites for PyTorch and SNNTorch neural networks",
+    "contributors_all": "2",
+    "contributors_2025": "1",
+    "contributors_2024": "1",
+    "contributors_2023": "0"
   },
   {
     "repo_name": "onnx",
@@ -258,14 +398,22 @@
     "category": "machine learning interoperability",
     "github_about_section": "Open standard for machine learning interoperability",
     "homepage_link": "https://onnx.ai",
-    "github_topic_closest_fit": "onnx"
+    "github_topic_closest_fit": "onnx",
+    "contributors_all": "370",
+    "contributors_2025": "56",
+    "contributors_2024": "45",
+    "contributors_2023": "61"
   },
   {
     "repo_name": "executorch",
     "repo_link": "https://github.com/pytorch/executorch",
     "category": "model compiler",
     "github_about_section": "On-device AI across mobile, embedded and edge for PyTorch",
-    "homepage_link": "https://executorch.ai"
+    "homepage_link": "https://executorch.ai",
+    "contributors_all": "437",
+    "contributors_2025": "267",
+    "contributors_2024": "243",
+    "contributors_2023": "77"
   },
   {
     "repo_name": "cutlass",
@@ -273,7 +421,11 @@
     "category": "parallel computing",
     "github_about_section": "CUDA Templates and Python DSLs for High-Performance Linear Algebra",
     "homepage_link": "https://docs.nvidia.com/cutlass/index.html",
-    "github_topic_closest_fit": "parallel-programming"
+    "github_topic_closest_fit": "parallel-programming",
+    "contributors_all": "238",
+    "contributors_2025": "94",
+    "contributors_2024": "64",
+    "contributors_2023": "66"
   },
   {
     "repo_name": "ThunderKittens",
@@ -281,7 +433,11 @@
     "category": "parallel computing",
     "github_about_section": "Tile primitives for speedy kernels",
     "homepage_link": "https://hazyresearch.stanford.edu/blog/2024-10-29-tk2",
-    "github_topic_closest_fit": "parallel-programming"
+    "github_topic_closest_fit": "parallel-programming",
+    "contributors_all": "34",
+    "contributors_2025": "29",
+    "contributors_2024": "13",
+    "contributors_2023": "0"
   },
   {
     "repo_name": "helion",
@@ -289,14 +445,22 @@
     "category": "parallel computing dsl",
     "github_about_section": "A Python-embedded DSL that makes it easy to write fast, scalable ML kernels with minimal boilerplate.",
     "homepage_link": "https://helionlang.com",
-    "github_topic_closest_fit": "parallel-programming"
+    "github_topic_closest_fit": "parallel-programming",
+    "contributors_all": "49",
+    "contributors_2025": "49",
+    "contributors_2024": "0",
+    "contributors_2023": "0"
   },
   {
     "repo_name": "TileIR",
     "repo_link": "https://github.com/microsoft/TileIR",
     "category": "parallel computing dsl",
     "github_about_section": "TileIR (tile-ir) is a concise domain-specific IR designed to streamline the development of high-performance GPU/CPU kernels (e.g., GEMM, Dequant GEMM, FlashAttention, LinearAttention). By employing a Pythonic syntax with an underlying compiler infrastructure on top of TVM, TileIR allows developers to focus on productivity without sacrificing the low-level optimizations necessary for state-of-the-art performance.",
-    "github_topic_closest_fit": "parallel-programming"
+    "github_topic_closest_fit": "parallel-programming",
+    "contributors_all": "10",
+    "contributors_2025": "10",
+    "contributors_2024": "1",
+    "contributors_2023": "0"
   },
   {
     "repo_name": "tilelang",
@@ -304,7 +468,11 @@
     "category": "parallel computing dsl",
     "github_about_section": "Domain-specific language designed to streamline the development of high-performance GPU/CPU/Accelerators kernels",
     "homepage_link": "https://tilelang.com",
-    "github_topic_closest_fit": "parallel-programming"
+    "github_topic_closest_fit": "parallel-programming",
+    "contributors_all": "90",
+    "contributors_2025": "89",
+    "contributors_2024": "1",
+    "contributors_2023": "0"
   },
   {
     "repo_name": "triton",
@@ -312,14 +480,22 @@
     "category": "parallel computing dsl",
     "github_about_section": "Development repository for the Triton language and compiler",
     "homepage_link": "https://triton-lang.org",
-    "github_topic_closest_fit": "parallel-programming"
+    "github_topic_closest_fit": "parallel-programming",
+    "contributors_all": "522",
+    "contributors_2025": "233",
+    "contributors_2024": "206",
+    "contributors_2023": "159"
   },
   {
     "repo_name": "cupti",
     "repo_link": "https://github.com/cwpearson/cupti",
     "category": "performance testing",
     "github_about_section": "Profile how CUDA applications create and modify data in memory.",
-    "github_topic_closest_fit": "profiling"
+    "github_topic_closest_fit": "profiling",
+    "contributors_all": "1",
+    "contributors_2025": "0",
+    "contributors_2024": "0",
+    "contributors_2023": "0"
   },
   {
     "repo_name": "hatchet",
@@ -327,7 +503,11 @@
     "category": "performance testing",
     "github_about_section": "Graph-indexed Pandas DataFrames for analyzing hierarchical performance data",
     "homepage_link": "https://llnl-hatchet.readthedocs.io",
-    "github_topic_closest_fit": "profiling"
+    "github_topic_closest_fit": "profiling",
+    "contributors_all": "25",
+    "contributors_2025": "3",
+    "contributors_2024": "6",
+    "contributors_2023": "8"
   },
   {
     "repo_name": "intelliperf",
@@ -335,7 +515,11 @@
     "category": "performance testing",
     "github_about_section": "Automated bottleneck detection and solution orchestration",
     "homepage_link": "https://arxiv.org/html/2508.20258v1",
-    "github_topic_closest_fit": "profiling"
+    "github_topic_closest_fit": "profiling",
+    "contributors_all": "7",
+    "contributors_2025": "7",
+    "contributors_2024": "0",
+    "contributors_2023": "0"
   },
   {
     "repo_name": "omnitrace",
@@ -343,7 +527,11 @@
     "category": "performance testing",
     "github_about_section": "Omnitrace: Application Profiling, Tracing, and Analysis",
     "homepage_link": "https://rocm.docs.amd.com/projects/omnitrace",
-    "github_topic_closest_fit": "profiling"
+    "github_topic_closest_fit": "profiling",
+    "contributors_all": "16",
+    "contributors_2025": "2",
+    "contributors_2024": "12",
+    "contributors_2023": "2"
   },
   {
     "repo_name": "jax",
@@ -351,7 +539,11 @@
     "category": "scientific computing",
     "github_about_section": "Composable transformations of Python+NumPy programs: differentiate, vectorize, JIT to GPU/TPU, and more",
     "homepage_link": "https://docs.jax.dev",
-    "github_topic_closest_fit": "scientific-computing"
+    "github_topic_closest_fit": "scientific-computing",
+    "contributors_all": "997",
+    "contributors_2025": "312",
+    "contributors_2024": "280",
+    "contributors_2023": "202"
   },
   {
     "repo_name": "numpy",
@@ -359,7 +551,11 @@
     "category": "scientific computing",
     "github_about_section": "The fundamental package for scientific computing with Python.",
     "homepage_link": "https://numpy.org",
-    "github_topic_closest_fit": "scientific-computing"
+    "github_topic_closest_fit": "scientific-computing",
+    "contributors_all": "2172",
+    "contributors_2025": "235",
+    "contributors_2024": "233",
+    "contributors_2023": "252"
   },
   {
     "repo_name": "scipy",
@@ -367,7 +563,11 @@
     "category": "scientific computing",
     "github_about_section": "SciPy library main repository",
     "homepage_link": "https://scipy.org",
-    "github_topic_closest_fit": "scientific-computing"
+    "github_topic_closest_fit": "scientific-computing",
+    "contributors_all": "1973",
+    "contributors_2025": "210",
+    "contributors_2024": "251",
+    "contributors_2023": "245"
   },
   {
     "repo_name": "elasticsearch",
@@ -375,7 +575,11 @@
     "category": "search engine",
     "github_about_section": "Free and Open Source, Distributed, RESTful Search Engine",
     "homepage_link": "https://elastic.co/products/elasticsearch",
-    "github_topic_closest_fit": "search-engine"
+    "github_topic_closest_fit": "search-engine",
+    "contributors_all": "2297",
+    "contributors_2025": "316",
+    "contributors_2024": "284",
+    "contributors_2023": "270"
   },
   {
     "repo_name": "jupyterlab",
@@ -383,7 +587,11 @@
     "category": "user interface",
     "github_about_section": "JupyterLab computational environment.",
     "homepage_link": "https://jupyterlab.readthedocs.io",
-    "github_topic_closest_fit": "jupyter"
+    "github_topic_closest_fit": "jupyter",
+    "contributors_all": "698",
+    "contributors_2025": "77",
+    "contributors_2024": "85",
+    "contributors_2023": "100"
   },
   {
     "repo_name": "milvus",
@@ -391,38 +599,62 @@
     "category": "vector database",
     "github_about_section": "Milvus is a high-performance, cloud-native vector database built for scalable vector ANN search",
     "homepage_link": "https://milvus.io",
-    "github_topic_closest_fit": "vector-search"
+    "github_topic_closest_fit": "vector-search",
+    "contributors_all": "387",
+    "contributors_2025": "95",
+    "contributors_2024": "84",
+    "contributors_2023": "72"
   },
   {
     "repo_name": "accelerate",
     "repo_link": "https://github.com/huggingface/accelerate",
     "github_about_section": "A simple way to launch, train, and use PyTorch models on almost any device and distributed configuration, automatic mixed precision (including fp8), and easy-to-configure FSDP and DeepSpeed support.",
-    "homepage_link": "https://huggingface.co/docs/accelerate"
+    "homepage_link": "https://huggingface.co/docs/accelerate",
+    "contributors_all": "392",
+    "contributors_2025": "97",
+    "contributors_2024": "124",
+    "contributors_2023": "149"
   },
   {
     "repo_name": "aiter",
     "repo_link": "https://github.com/ROCm/aiter",
     "github_about_section": "AI Tensor Engine for ROCm",
-    "homepage_link": "https://rocm.blogs.amd.com/software-tools-optimization/aiter-ai-tensor-engine/README.html"
+    "homepage_link": "https://rocm.blogs.amd.com/software-tools-optimization/aiter-ai-tensor-engine/README.html",
+    "contributors_all": "151",
+    "contributors_2025": "145",
+    "contributors_2024": "10",
+    "contributors_2023": "0"
   },
   {
     "repo_name": "ao",
     "repo_link": "https://github.com/pytorch/ao",
     "github_about_section": "PyTorch native quantization and sparsity for training and inference",
     "homepage_link": "https://pytorch.org/ao",
-    "github_topic_closest_fit": "quantization"
+    "github_topic_closest_fit": "quantization",
+    "contributors_all": "178",
+    "contributors_2025": "114",
+    "contributors_2024": "100",
+    "contributors_2023": "5"
   },
   {
     "repo_name": "burn",
     "repo_link": "https://github.com/tracel-ai/burn",
     "github_about_section": "Burn is a next generation tensor library and Deep Learning Framework that doesn't compromise on flexibility, efficiency and portability.",
-    "homepage_link": "https://burn.dev"
+    "homepage_link": "https://burn.dev",
+    "contributors_all": "237",
+    "contributors_2025": "99",
+    "contributors_2024": "104",
+    "contributors_2023": "62"
   },
   {
     "repo_name": "ccache",
     "repo_link": "https://github.com/ccache/ccache",
     "github_about_section": "ccache - a fast compiler cache",
-    "homepage_link": "https://ccache.dev"
+    "homepage_link": "https://ccache.dev",
+    "contributors_all": "218",
+    "contributors_2025": "20",
+    "contributors_2024": "28",
+    "contributors_2023": "22"
   },
   {
     "repo_name": "ComfyUI",
@@ -430,14 +662,22 @@
     "category": "user interface",
     "github_about_section": "The most powerful and modular diffusion model GUI, api and backend with a graph/nodes interface.",
     "homepage_link": "https://comfy.org",
-    "github_topic_closest_fit": "stable-diffusion"
+    "github_topic_closest_fit": "stable-diffusion",
+    "contributors_all": "278",
+    "contributors_2025": "108",
+    "contributors_2024": "119",
+    "contributors_2023": "94"
   },
   {
     "repo_name": "composable_kernel",
     "repo_link": "https://github.com/ROCm/composable_kernel",
     "category": "gpu kernels",
     "github_about_section": "Composable Kernel: Performance Portable Programming Model for Machine Learning Tensor Operators",
-    "homepage_link": "https://rocm.docs.amd.com/projects/composable_kernel"
+    "homepage_link": "https://rocm.docs.amd.com/projects/composable_kernel",
+    "contributors_all": "190",
+    "contributors_2025": "140",
+    "contributors_2024": "58",
+    "contributors_2023": "33"
   },
   {
     "repo_name": "cudnn-frontend",
@@ -445,7 +685,11 @@
     "category": "parallel computing",
     "github_about_section": "cudnn_frontend provides a c++ wrapper for the cudnn backend API and samples on how to use it",
     "homepage_link": "https://developer.nvidia.com/cudnn",
-    "github_topic_closest_fit": "parallel-programming"
+    "github_topic_closest_fit": "parallel-programming",
+    "contributors_all": "12",
+    "contributors_2025": "6",
+    "contributors_2024": "5",
+    "contributors_2023": "1"
   },
   {
     "repo_name": "cuJSON",
@@ -453,13 +697,21 @@
     "category": "library leveraging parallel compute",
     "github_about_section": "cuJSON: A Highly Parallel JSON Parser for GPUs",
     "homepage_link": "https://dl.acm.org/doi/10.1145/3760250.3762222",
-    "github_topic_closest_fit": "json-parser"
+    "github_topic_closest_fit": "json-parser",
+    "contributors_all": "2",
+    "contributors_2025": "2",
+    "contributors_2024": "2",
+    "contributors_2023": "0"
   },
   {
     "repo_name": "DeepSpeed",
     "repo_link": "https://github.com/deepspeedai/DeepSpeed",
     "github_about_section": "DeepSpeed is a deep learning optimization library that makes distributed training and inference easy, efficient, and effective.",
-    "homepage_link": "https://deepspeed.ai"
+    "homepage_link": "https://deepspeed.ai",
+    "contributors_all": "442",
+    "contributors_2025": "96",
+    "contributors_2024": "134",
+    "contributors_2023": "165"
   },
   {
     "repo_name": "dstack",
@@ -467,7 +719,11 @@
     "category": "gpu provisioning and orchestration",
     "github_about_section": "dstack is an open-source control plane for running development, training, and inference jobs on GPUs-across hyperscalers, neoclouds, or on-prem.",
     "homepage_link": "https://dstack.ai",
-    "github_topic_closest_fit": "orchestration"
+    "github_topic_closest_fit": "orchestration",
+    "contributors_all": "69",
+    "contributors_2025": "28",
+    "contributors_2024": "42",
+    "contributors_2023": "14"
   },
   {
     "repo_name": "flashinfer",
@@ -475,7 +731,11 @@
     "category": "gpu kernels",
     "github_about_section": "FlashInfer: Kernel Library for LLM Serving",
     "homepage_link": "https://flashinfer.ai",
-    "github_topic_closest_fit": "attention"
+    "github_topic_closest_fit": "attention",
+    "contributors_all": "205",
+    "contributors_2025": "158",
+    "contributors_2024": "50",
+    "contributors_2023": "11"
   },
   {
     "repo_name": "FTorch",
@@ -483,32 +743,52 @@
     "category": "wrapper",
     "github_about_section": "A library for directly calling PyTorch ML models from Fortran.",
     "homepage_link": "https://cambridge-iccs.github.io/FTorch",
-    "github_topic_closest_fit": "machine-learning"
+    "github_topic_closest_fit": "machine-learning",
+    "contributors_all": "20",
+    "contributors_2025": "11",
+    "contributors_2024": "8",
+    "contributors_2023": "9"
   },
   {
     "repo_name": "GEAK-agent",
     "repo_link": "https://github.com/AMD-AGI/GEAK-agent",
     "category": "agent",
     "github_about_section": "It is an LLM-based AI agent, which can write correct and efficient gpu kernels automatically.",
-    "github_topic_closest_fit": "ai-agents"
+    "github_topic_closest_fit": "ai-agents",
+    "contributors_all": "9",
+    "contributors_2025": "9",
+    "contributors_2024": "0",
+    "contributors_2023": "0"
   },
   {
     "repo_name": "hhvm",
     "repo_link": "https://github.com/facebook/hhvm",
     "github_about_section": "A virtual machine for executing programs written in Hack.",
-    "homepage_link": "https://hhvm.com"
+    "homepage_link": "https://hhvm.com",
+    "contributors_all": "2624",
+    "contributors_2025": "692",
+    "contributors_2024": "648",
+    "contributors_2023": "604"
   },
   {
     "repo_name": "hip",
     "repo_link": "https://github.com/ROCm/hip",
     "github_about_section": "HIP: C++ Heterogeneous-Compute Interface for Portability",
-    "homepage_link": "https://rocmdocs.amd.com/projects/HIP"
+    "homepage_link": "https://rocmdocs.amd.com/projects/HIP",
+    "contributors_all": "288",
+    "contributors_2025": "46",
+    "contributors_2024": "31",
+    "contributors_2023": "25"
   },
   {
     "repo_name": "hipCUB",
     "repo_link": "https://github.com/ROCm/hipCUB",
     "github_about_section": "[DEPRECATED] Moved to ROCm/rocm-libraries repo",
-    "homepage_link": "https://github.com/ROCm/rocm-libraries"
+    "homepage_link": "https://github.com/ROCm/rocm-libraries",
+    "contributors_all": "54",
+    "contributors_2025": "10",
+    "contributors_2024": "19",
+    "contributors_2023": "13"
   },
   {
     "repo_name": "IMO2025",
@@ -516,7 +796,11 @@
     "category": "formal mathematical reasoning",
     "github_about_section": "Harmonic's model Aristotle achieved gold medal performance, solving 5 problems. This repository contains the lean statement files and proofs for Problems 1-5.",
     "homepage_link": "https://harmonic.fun",
-    "github_topic_closest_fit": "lean"
+    "github_topic_closest_fit": "lean",
+    "contributors_all": "2",
+    "contributors_2025": "2",
+    "contributors_2024": "0",
+    "contributors_2023": "0"
   },
   {
     "repo_name": "kubernetes",
@@ -524,7 +808,11 @@
     "category": "container orchestration",
     "github_about_section": "Production-Grade Container Scheduling and Management",
     "homepage_link": "https://kubernetes.io",
-    "github_topic_closest_fit": "kubernetes"
+    "github_topic_closest_fit": "kubernetes",
+    "contributors_all": "5041",
+    "contributors_2025": "509",
+    "contributors_2024": "498",
+    "contributors_2023": "565"
   },
   {
     "repo_name": "lapack",
@@ -532,7 +820,11 @@
     "category": "linear algebra",
     "github_about_section": "LAPACK is a library of Fortran subroutines for solving the most commonly occurring problems in numerical linear algebra.",
     "homepage_link": "https://netlib.org/lapack",
-    "github_topic_closest_fit": "linear-algebra"
+    "github_topic_closest_fit": "linear-algebra",
+    "contributors_all": "178",
+    "contributors_2025": "20",
+    "contributors_2024": "24",
+    "contributors_2023": "42"
   },
   {
     "repo_name": "lean4",
@@ -540,7 +832,11 @@
     "category": "theorem prover",
     "github_about_section": "Lean 4 programming language and theorem prover",
     "homepage_link": "https://lean-lang.org",
-    "github_topic_closest_fit": "lean"
+    "github_topic_closest_fit": "lean",
+    "contributors_all": "278",
+    "contributors_2025": "110",
+    "contributors_2024": "85",
+    "contributors_2023": "64"
   },
   {
     "repo_name": "letta",
@@ -548,37 +844,61 @@
     "category": "agent",
     "github_about_section": "Letta is the platform for building stateful agents: open AI with advanced memory that can learn and self-improve over time.",
     "homepage_link": "https://docs.letta.com",
-    "github_topic_closest_fit": "ai-agents"
+    "github_topic_closest_fit": "ai-agents",
+    "contributors_all": "157",
+    "contributors_2025": "56",
+    "contributors_2024": "75",
+    "contributors_2023": "47"
   },
   {
     "repo_name": "lightning-thunder",
     "repo_link": "https://github.com/Lightning-AI/lightning-thunder",
-    "github_about_section": "PyTorch compiler that accelerates training and inference. Get built-in optimizations for performance, memory, parallelism, and easily write your own."
+    "github_about_section": "PyTorch compiler that accelerates training and inference. Get built-in optimizations for performance, memory, parallelism, and easily write your own.",
+    "contributors_all": "76",
+    "contributors_2025": "44",
+    "contributors_2024": "47",
+    "contributors_2023": "29"
   },
   {
     "repo_name": "LMCache",
     "repo_link": "https://github.com/LMCache/LMCache",
     "github_about_section": "Supercharge Your LLM with the Fastest KV Cache Layer",
-    "homepage_link": "https://lmcache.ai"
+    "homepage_link": "https://lmcache.ai",
+    "contributors_all": "152",
+    "contributors_2025": "144",
+    "contributors_2024": "18",
+    "contributors_2023": "0"
   },
   {
     "repo_name": "mcp-agent",
     "repo_link": "https://github.com/lastmile-ai/mcp-agent",
     "category": "mcp",
     "github_about_section": "Build effective agents using Model Context Protocol and simple workflow patterns",
-    "github_topic_closest_fit": "mcp"
+    "github_topic_closest_fit": "mcp",
+    "contributors_all": "63",
+    "contributors_2025": "63",
+    "contributors_2024": "1",
+    "contributors_2023": "0"
   },
   {
     "repo_name": "metaflow",
     "repo_link": "https://github.com/Netflix/metaflow",
     "github_about_section": "Build, Manage and Deploy AI/ML Systems",
-    "homepage_link": "https://metaflow.org"
+    "homepage_link": "https://metaflow.org",
+    "contributors_all": "121",
+    "contributors_2025": "37",
+    "contributors_2024": "35",
+    "contributors_2023": "28"
   },
   {
     "repo_name": "MIOpen",
     "repo_link": "https://github.com/ROCm/MIOpen",
     "github_about_section": "[DEPRECATED] Moved to ROCm/rocm-libraries repo",
-    "homepage_link": "https://github.com/ROCm/rocm-libraries"
+    "homepage_link": "https://github.com/ROCm/rocm-libraries",
+    "contributors_all": "204",
+    "contributors_2025": "47",
+    "contributors_2024": "62",
+    "contributors_2023": "44"
   },
   {
     "repo_name": "modelcontextprotocol",
@@ -586,7 +906,11 @@
     "category": "mcp",
     "github_about_section": "Specification and documentation for the Model Context Protocol",
     "homepage_link": "https://modelcontextprotocol.io",
-    "github_topic_closest_fit": "mcp"
+    "github_topic_closest_fit": "mcp",
+    "contributors_all": "327",
+    "contributors_2025": "298",
+    "contributors_2024": "42",
+    "contributors_2023": "0"
   },
   {
     "repo_name": "modular",
@@ -594,143 +918,239 @@
     "category": "parallel computing",
     "github_about_section": "The Modular Platform (includes MAX & Mojo)",
     "homepage_link": "https://docs.modular.com",
-    "github_topic_closest_fit": "parallel-programming"
+    "github_topic_closest_fit": "parallel-programming",
+    "contributors_all": "366",
+    "contributors_2025": "222",
+    "contributors_2024": "205",
+    "contributors_2023": "99"
   },
   {
     "repo_name": "monarch",
     "repo_link": "https://github.com/meta-pytorch/monarch",
     "github_about_section": "PyTorch Single Controller",
-    "homepage_link": "https://meta-pytorch.org/monarch"
+    "homepage_link": "https://meta-pytorch.org/monarch",
+    "contributors_all": "85",
+    "contributors_2025": "85",
+    "contributors_2024": "0",
+    "contributors_2023": "0"
   },
   {
     "repo_name": "Mooncake",
     "repo_link": "https://github.com/kvcache-ai/Mooncake",
     "github_about_section": "Mooncake is the serving platform for Kimi, a leading LLM service provided by Moonshot AI.",
     "homepage_link": "https://kvcache-ai.github.io/Mooncake",
-    "github_topic_closest_fit": "inference"
+    "github_topic_closest_fit": "inference",
+    "contributors_all": "138",
+    "contributors_2025": "133",
+    "contributors_2024": "13",
+    "contributors_2023": "0"
   },
   {
     "repo_name": "nccl",
     "repo_link": "https://github.com/NVIDIA/nccl",
     "github_about_section": "Optimized primitives for collective multi-GPU communication",
-    "homepage_link": "https://docs.nvidia.com/deeplearning/nccl/user-guide/docs/index.html"
+    "homepage_link": "https://docs.nvidia.com/deeplearning/nccl/user-guide/docs/index.html",
+    "contributors_all": "51",
+    "contributors_2025": "7",
+    "contributors_2024": "5",
+    "contributors_2023": "6"
   },
   {
     "repo_name": "neuronx-distributed-inference",
-    "repo_link": "https://github.com/aws-neuron/neuronx-distributed-inference"
+    "repo_link": "https://github.com/aws-neuron/neuronx-distributed-inference",
+    "contributors_all": "11",
+    "contributors_2025": "9",
+    "contributors_2024": "3",
+    "contributors_2023": "0"
   },
   {
     "repo_name": "nixl",
     "repo_link": "https://github.com/ai-dynamo/nixl",
-    "github_about_section": "NVIDIA Inference Xfer Library (NIXL)"
+    "github_about_section": "NVIDIA Inference Xfer Library (NIXL)",
+    "contributors_all": "78",
+    "contributors_2025": "78",
+    "contributors_2024": "0",
+    "contributors_2023": "0"
   },
   {
     "repo_name": "ome",
     "repo_link": "https://github.com/sgl-project/ome",
     "github_about_section": "OME is a Kubernetes operator for enterprise-grade management and serving of Large Language Models (LLMs)",
     "homepage_link": "http://docs.sglang.ai/ome",
-    "github_topic_closest_fit": "k8s"
+    "github_topic_closest_fit": "k8s",
+    "contributors_all": "28",
+    "contributors_2025": "28",
+    "contributors_2024": "0",
+    "contributors_2023": "0"
   },
   {
     "repo_name": "ondemand",
     "repo_link": "https://github.com/OSC/ondemand",
     "github_about_section": "Supercomputing. Seamlessly. Open, Interactive HPC Via the Web",
     "homepage_link": "https://openondemand.org",
-    "github_topic_closest_fit": "hpc"
+    "github_topic_closest_fit": "hpc",
+    "contributors_all": "117",
+    "contributors_2025": "43",
+    "contributors_2024": "23",
+    "contributors_2023": "21"
   },
   {
     "repo_name": "oneDPL",
     "repo_link": "https://github.com/uxlfoundation/oneDPL",
     "github_about_section": "oneAPI DPC++ Library (oneDPL)",
-    "homepage_link": "https://software.intel.com/content/www/us/en/develop/tools/oneapi/components/dpc-library.html"
+    "homepage_link": "https://software.intel.com/content/www/us/en/develop/tools/oneapi/components/dpc-library.html",
+    "contributors_all": "67",
+    "contributors_2025": "17",
+    "contributors_2024": "29",
+    "contributors_2023": "28"
   },
   {
     "repo_name": "openevolve",
     "repo_link": "https://github.com/codelion/openevolve",
     "github_about_section": "Open-source implementation of AlphaEvolve",
-    "github_topic_closest_fit": "genetic-algorithm"
+    "github_topic_closest_fit": "genetic-algorithm",
+    "contributors_all": "46",
+    "contributors_2025": "46",
+    "contributors_2024": "0",
+    "contributors_2023": "0"
   },
   {
     "repo_name": "ort",
     "repo_link": "https://github.com/pytorch/ort",
-    "github_about_section": "Accelerate PyTorch models with ONNX Runtime"
+    "github_about_section": "Accelerate PyTorch models with ONNX Runtime",
+    "contributors_all": "47",
+    "contributors_2025": "0",
+    "contributors_2024": "7",
+    "contributors_2023": "9"
   },
   {
     "repo_name": "peft",
     "repo_link": "https://github.com/huggingface/peft",
     "github_about_section": "PEFT: State-of-the-art Parameter-Efficient Fine-Tuning.",
     "homepage_link": "https://huggingface.co/docs/peft",
-    "github_topic_closest_fit": "lora"
+    "github_topic_closest_fit": "lora",
+    "contributors_all": "272",
+    "contributors_2025": "69",
+    "contributors_2024": "111",
+    "contributors_2023": "115"
   },
   {
     "repo_name": "Primus-Turbo",
-    "repo_link": "https://github.com/AMD-AGI/Primus-Turbo"
+    "repo_link": "https://github.com/AMD-AGI/Primus-Turbo",
+    "contributors_all": "12",
+    "contributors_2025": "12",
+    "contributors_2024": "0",
+    "contributors_2023": "0"
   },
   {
     "repo_name": "pybind11",
     "repo_link": "https://github.com/pybind/pybind11",
     "github_about_section": "Seamless operability between C++11 and Python",
     "homepage_link": "https://pybind11.readthedocs.io",
-    "github_topic_closest_fit": "bindings"
+    "github_topic_closest_fit": "bindings",
+    "contributors_all": "404",
+    "contributors_2025": "43",
+    "contributors_2024": "45",
+    "contributors_2023": "42"
   },
   {
     "repo_name": "RaBitQ",
     "repo_link": "https://github.com/gaoj0017/RaBitQ",
     "github_about_section": "[SIGMOD 2024] RaBitQ: Quantizing High-Dimensional Vectors with a Theoretical Error Bound for Approximate Nearest Neighbor Search",
     "homepage_link": "https://github.com/VectorDB-NTU/RaBitQ-Library",
-    "github_topic_closest_fit": "nearest-neighbor-search"
+    "github_topic_closest_fit": "nearest-neighbor-search",
+    "contributors_all": "2",
+    "contributors_2025": "2",
+    "contributors_2024": "1",
+    "contributors_2023": "0"
   },
   {
     "repo_name": "rdma-core",
     "repo_link": "https://github.com/linux-rdma/rdma-core",
-    "github_about_section": "RDMA core userspace libraries and daemons"
+    "github_about_section": "RDMA core userspace libraries and daemons",
+    "contributors_all": "437",
+    "contributors_2025": "58",
+    "contributors_2024": "61",
+    "contributors_2023": "66"
   },
   {
     "repo_name": "rocFFT",
     "repo_link": "https://github.com/ROCm/rocFFT",
     "github_about_section": "[DEPRECATED] Moved to ROCm/rocm-libraries repo",
-    "homepage_link": "https://github.com/ROCm/rocm-libraries"
+    "homepage_link": "https://github.com/ROCm/rocm-libraries",
+    "contributors_all": "81",
+    "contributors_2025": "17",
+    "contributors_2024": "20",
+    "contributors_2023": "19"
   },
   {
     "repo_name": "ROCm",
     "repo_link": "https://github.com/ROCm/ROCm",
     "github_about_section": "AMD ROCm Software - GitHub Home",
-    "homepage_link": "https://rocm.docs.amd.com"
+    "homepage_link": "https://rocm.docs.amd.com",
+    "contributors_all": "166",
+    "contributors_2025": "67",
+    "contributors_2024": "61",
+    "contributors_2023": "44"
   },
   {
     "repo_name": "rocm-systems",
     "repo_link": "https://github.com/ROCm/rocm-systems",
-    "github_about_section": "super repo for rocm systems projects"
+    "github_about_section": "super repo for rocm systems projects",
+    "contributors_all": "1032",
+    "contributors_2025": "440",
+    "contributors_2024": "323",
+    "contributors_2023": "204"
   },
   {
     "repo_name": "rocPRIM",
     "repo_link": "https://github.com/ROCm/rocPRIM",
     "github_about_section": "[DEPRECATED] Moved to ROCm/rocm-libraries repo",
-    "homepage_link": "https://github.com/ROCm/rocm-libraries"
+    "homepage_link": "https://github.com/ROCm/rocm-libraries",
+    "contributors_all": "76",
+    "contributors_2025": "12",
+    "contributors_2024": "28",
+    "contributors_2023": "15"
   },
   {
     "repo_name": "rocRAND",
     "repo_link": "https://github.com/ROCm/rocRAND",
     "github_about_section": "[DEPRECATED] Moved to ROCm/rocm-libraries repo",
-    "homepage_link": "https://github.com/ROCm/rocm-libraries"
+    "homepage_link": "https://github.com/ROCm/rocm-libraries",
+    "contributors_all": "85",
+    "contributors_2025": "10",
+    "contributors_2024": "32",
+    "contributors_2023": "26"
   },
   {
     "repo_name": "rocSOLVER",
     "repo_link": "https://github.com/ROCm/rocSOLVER",
     "github_about_section": "[DEPRECATED] Moved to ROCm/rocm-libraries repo",
-    "homepage_link": "https://github.com/ROCm/rocm-libraries"
+    "homepage_link": "https://github.com/ROCm/rocm-libraries",
+    "contributors_all": "59",
+    "contributors_2025": "20",
+    "contributors_2024": "23",
+    "contributors_2023": "15"
   },
   {
     "repo_name": "rocSPARSE",
     "repo_link": "https://github.com/ROCm/rocSPARSE",
     "github_about_section": "[DEPRECATED] Moved to ROCm/rocm-libraries repo",
-    "homepage_link": "https://github.com/ROCm/rocm-libraries"
+    "homepage_link": "https://github.com/ROCm/rocm-libraries",
+    "contributors_all": "65",
+    "contributors_2025": "19",
+    "contributors_2024": "24",
+    "contributors_2023": "18"
   },
   {
     "repo_name": "roctracer",
     "repo_link": "https://github.com/ROCm/roctracer",
     "github_about_section": "[DEPRECATED] Moved to ROCm/rocm-systems repo",
-    "homepage_link": "https://github.com/ROCm/rocm-systems"
+    "homepage_link": "https://github.com/ROCm/rocm-systems",
+    "contributors_all": "45",
+    "contributors_2025": "8",
+    "contributors_2024": "11",
+    "contributors_2023": "6"
   },
   {
     "repo_name": "Self-Forcing",
@@ -738,21 +1158,33 @@
     "category": "video generation",
     "github_about_section": "Official codebase for \"Self Forcing: Bridging Training and Inference in Autoregressive Video Diffusion\" (NeurIPS 2025 Spotlight)",
     "homepage_link": "https://self-forcing.github.io",
-    "github_topic_closest_fit": "diffusion-models"
+    "github_topic_closest_fit": "diffusion-models",
+    "contributors_all": "4",
+    "contributors_2025": "4",
+    "contributors_2024": "0",
+    "contributors_2023": "0"
   },
   {
     "repo_name": "server",
     "repo_link": "https://github.com/triton-inference-server/server",
     "github_about_section": "The Triton Inference Server provides an optimized cloud and edge inferencing solution.",
     "homepage_link": "https://docs.nvidia.com/deeplearning/triton-inference-server/user-guide/docs/index.html",
-    "github_topic_closest_fit": "inference"
+    "github_topic_closest_fit": "inference",
+    "contributors_all": "147",
+    "contributors_2025": "24",
+    "contributors_2024": "36",
+    "contributors_2023": "34"
   },
   {
     "repo_name": "spark",
     "repo_link": "https://github.com/apache/spark",
     "github_about_section": "Apache Spark - A unified analytics engine for large-scale data processing",
     "homepage_link": "https://spark.apache.org",
-    "github_topic_closest_fit": "big-data"
+    "github_topic_closest_fit": "big-data",
+    "contributors_all": "3083",
+    "contributors_2025": "322",
+    "contributors_2024": "300",
+    "contributors_2023": "336"
   },
   {
     "repo_name": "StreamDiffusion",
@@ -760,7 +1192,11 @@
     "category": "image generation",
     "github_about_section": "StreamDiffusion: A Pipeline-Level Solution for Real-Time Interactive Generation",
     "homepage_link": "https://arxiv.org/abs/2312.12491",
-    "github_topic_closest_fit": "diffusion-models"
+    "github_topic_closest_fit": "diffusion-models",
+    "contributors_all": "29",
+    "contributors_2025": "0",
+    "contributors_2024": "9",
+    "contributors_2023": "25"
   },
   {
     "repo_name": "streamv2v",
@@ -768,7 +1204,11 @@
     "category": "video generation",
     "github_about_section": "Official Pytorch implementation of StreamV2V.",
     "homepage_link": "https://jeff-liangf.github.io/projects/streamv2v",
-    "github_topic_closest_fit": "diffusion-models"
+    "github_topic_closest_fit": "diffusion-models",
+    "contributors_all": "7",
+    "contributors_2025": "3",
+    "contributors_2024": "6",
+    "contributors_2023": "0"
   },
   {
     "repo_name": "synthetic-data-kit",
@@ -776,63 +1216,98 @@
     "category": "synthetic data generation",
     "github_about_section": "Tool for generating high quality Synthetic datasets",
     "homepage_link": "https://pypi.org/project/synthetic-data-kit",
-    "github_topic_closest_fit": "synthetic-dataset-generation"
+    "github_topic_closest_fit": "synthetic-dataset-generation",
+    "contributors_all": "15",
+    "contributors_2025": "15",
+    "contributors_2024": "0",
+    "contributors_2023": "0"
   },
   {
     "repo_name": "Tensile",
     "repo_link": "https://github.com/ROCm/Tensile",
     "github_about_section": "[DEPRECATED] Moved to ROCm/rocm-libraries repo",
-    "homepage_link": "https://github.com/ROCm/rocm-libraries"
+    "homepage_link": "https://github.com/ROCm/rocm-libraries",
+    "contributors_all": "137",
+    "contributors_2025": "16",
+    "contributors_2024": "25",
+    "contributors_2023": "22"
   },
   {
     "repo_name": "tflite-micro",
     "repo_link": "https://github.com/tensorflow/tflite-micro",
-    "github_about_section": "Infrastructure to enable deployment of ML models to low-power resource-constrained embedded targets (including microcontrollers and digital signal processors)."
+    "github_about_section": "Infrastructure to enable deployment of ML models to low-power resource-constrained embedded targets (including microcontrollers and digital signal processors).",
+    "contributors_all": "111",
+    "contributors_2025": "19",
+    "contributors_2024": "25",
+    "contributors_2023": "31"
   },
   {
     "repo_name": "torchdynamo",
     "repo_link": "https://github.com/pytorch/torchdynamo",
-    "github_about_section": "A Python-level JIT compiler designed to make unmodified PyTorch programs faster."
+    "github_about_section": "A Python-level JIT compiler designed to make unmodified PyTorch programs faster.",
+    "contributors_all": "63",
+    "contributors_2025": "0",
+    "contributors_2024": "1",
+    "contributors_2023": "4"
   },
   {
     "repo_name": "torchtitan",
     "repo_link": "https://github.com/pytorch/torchtitan",
-    "github_about_section": "A PyTorch native platform for training generative AI models"
-  },
-  {
-    "repo_name": "torchtitan",
-    "repo_link": "https://github.com/AMD-AGI/torchtitan",
-    "github_about_section": "A PyTorch native platform for training generative AI models"
+    "github_about_section": "A PyTorch native platform for training generative AI models",
+    "contributors_all": "145",
+    "contributors_2025": "119",
+    "contributors_2024": "43",
+    "contributors_2023": "1"
   },
   {
     "repo_name": "transformers",
     "repo_link": "https://github.com/huggingface/transformers",
     "github_about_section": "Transformers: the model-definition framework for state-of-the-art machine learning models in text, vision, audio, and multimodal models, for both inference and training.",
-    "homepage_link": "https://huggingface.co/transformers"
+    "homepage_link": "https://huggingface.co/transformers",
+    "contributors_all": "3582",
+    "contributors_2025": "860",
+    "contributors_2024": "769",
+    "contributors_2023": "758"
   },
   {
     "repo_name": "Triton-distributed",
     "repo_link": "https://github.com/ByteDance-Seed/Triton-distributed",
     "github_about_section": "Distributed Compiler based on Triton for Parallel Systems",
-    "homepage_link": "https://triton-distributed.readthedocs.io"
+    "homepage_link": "https://triton-distributed.readthedocs.io",
+    "contributors_all": "30",
+    "contributors_2025": "30",
+    "contributors_2024": "0",
+    "contributors_2023": "0"
   },
   {
     "repo_name": "triton-runner",
     "repo_link": "https://github.com/toyaix/triton-runner",
     "github_about_section": "Multi-Level Triton Runner supporting Python, IR, PTX, and cubin.",
-    "homepage_link": "https://triton-runner.org"
+    "homepage_link": "https://triton-runner.org",
+    "contributors_all": "1",
+    "contributors_2025": "1",
+    "contributors_2024": "0",
+    "contributors_2023": "0"
   },
   {
     "repo_name": "tritonparse",
     "repo_link": "https://github.com/meta-pytorch/tritonparse",
     "github_about_section": "TritonParse: A Compiler Tracer, Visualizer, and Reproducer for Triton Kernels",
-    "homepage_link": "https://meta-pytorch.org/tritonparse"
+    "homepage_link": "https://meta-pytorch.org/tritonparse",
+    "contributors_all": "15",
+    "contributors_2025": "15",
+    "contributors_2024": "0",
+    "contributors_2023": "0"
   },
   {
     "repo_name": "trl",
     "repo_link": "https://github.com/huggingface/trl",
     "github_about_section": "Train transformer language models with reinforcement learning.",
-    "homepage_link": "http://hf.co/docs/trl"
+    "homepage_link": "http://hf.co/docs/trl",
+    "contributors_all": "433",
+    "contributors_2025": "189",
+    "contributors_2024": "154",
+    "contributors_2023": "122"
   },
   {
     "repo_name": "truss",
@@ -840,7 +1315,11 @@
     "category": "inference engine",
     "github_about_section": "The simplest way to serve AI/ML models in production",
     "homepage_link": "https://truss.baseten.co",
-    "github_topic_closest_fit": "inference"
+    "github_topic_closest_fit": "inference",
+    "contributors_all": "72",
+    "contributors_2025": "44",
+    "contributors_2024": "30",
+    "contributors_2023": "21"
   },
   {
     "repo_name": "unsloth",
@@ -848,7 +1327,11 @@
     "category": "fine tuning",
     "github_about_section": "Fine-tuning & Reinforcement Learning for LLMs. Train OpenAI gpt-oss, DeepSeek-R1, Qwen3, Gemma 3, TTS 2x faster with 70% less VRAM.",
     "homepage_link": "https://docs.unsloth.ai",
-    "github_topic_closest_fit": "fine-tuning"
+    "github_topic_closest_fit": "fine-tuning",
+    "contributors_all": "127",
+    "contributors_2025": "102",
+    "contributors_2024": "27",
+    "contributors_2023": "3"
   },
   {
     "repo_name": "verl",
@@ -856,7 +1339,11 @@
     "category": "reinforcement learning",
     "github_about_section": "verl: Volcano Engine Reinforcement Learning for LLMs",
     "homepage_link": "https://verl.readthedocs.io",
-    "github_topic_closest_fit": "deep-reinforcement-learning"
+    "github_topic_closest_fit": "deep-reinforcement-learning",
+    "contributors_all": "462",
+    "contributors_2025": "454",
+    "contributors_2024": "10",
+    "contributors_2023": "0"
   },
   {
     "repo_name": "Vulkan-Hpp",
@@ -864,7 +1351,11 @@
     "category": "graphics api",
     "github_about_section": "Open-Source Vulkan C++ API",
     "homepage_link": "https://vulkan.org",
-    "github_topic_closest_fit": "vulkan"
+    "github_topic_closest_fit": "vulkan",
+    "contributors_all": "102",
+    "contributors_2025": "21",
+    "contributors_2024": "15",
+    "contributors_2023": "15"
   },
   {
     "repo_name": "Vulkan-Tools",
@@ -872,7 +1363,11 @@
     "category": "graphics api",
     "github_about_section": "Vulkan Development Tools",
     "homepage_link": "https://vulkan.org",
-    "github_topic_closest_fit": "vulkan"
+    "github_topic_closest_fit": "vulkan",
+    "contributors_all": "248",
+    "contributors_2025": "20",
+    "contributors_2024": "24",
+    "contributors_2023": "24"
   },
   {
     "repo_name": "Vulkan-Docs",
@@ -880,7 +1375,11 @@
     "category": "graphics api",
     "github_about_section": "The Vulkan API Specification and related tools",
     "homepage_link": "https://vulkan.org",
-    "github_topic_closest_fit": "vulkan"
+    "github_topic_closest_fit": "vulkan",
+    "contributors_all": "141",
+    "contributors_2025": "18",
+    "contributors_2024": "21",
+    "contributors_2023": "34"
   },
   {
     "repo_name": "Wan2.2",
@@ -888,7 +1387,11 @@
     "category": "video generation",
     "github_about_section": "Wan: Open and Advanced Large-Scale Video Generative Models",
     "homepage_link": "https://wan.video",
-    "github_topic_closest_fit": "diffusion-models"
+    "github_topic_closest_fit": "diffusion-models",
+    "contributors_all": "14",
+    "contributors_2025": "14",
+    "contributors_2024": "0",
+    "contributors_2023": "0"
   },
   {
     "repo_name": "warp",
@@ -896,6 +1399,10 @@
     "category": "spatial computing",
     "github_about_section": "A Python framework for accelerated simulation, data generation and spatial computing.",
     "homepage_link": "https://nvidia.github.io/warp",
-    "github_topic_closest_fit": "physics-simulation"
+    "github_topic_closest_fit": "physics-simulation",
+    "contributors_all": "79",
+    "contributors_2025": "40",
+    "contributors_2024": "29",
+    "contributors_2023": "17"
   }
 ]