Fixed contributors to be int instead of string

PyTorchConference2025_GithubRepos.json

@@ -6,20 +6,20 @@
     "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",
-    "contributors_all": "332",
-    "contributors_2025": "319",
-    "contributors_2024": "32",
-    "contributors_2023": "0"
+    "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",
-    "contributors_all": "1381",
-    "contributors_2025": "397",
-    "contributors_2024": "223",
-    "contributors_2023": "230"
+    "contributors_all": 1381,
+    "contributors_2025": 397,
+    "contributors_2024": 223,
+    "contributors_2023": 230
   },
   {
     "repo_name": "flashinfer-bench",
@@ -28,10 +28,10 @@
     "github_about_section": "Building the Virtuous Cycle for AI-driven LLM Systems",
     "homepage_link": "https://bench.flashinfer.ai",
     "github_topic_closest_fit": "benchmark",
-    "contributors_all": "12",
-    "contributors_2025": "11",
-    "contributors_2024": "0",
-    "contributors_2023": "0"
+    "contributors_all": 12,
+    "contributors_2025": 11,
+    "contributors_2024": 0,
+    "contributors_2023": 0
   },
   {
     "repo_name": "KernelBench",
@@ -40,10 +40,10 @@
     "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",
-    "contributors_all": "19",
-    "contributors_2025": "16",
-    "contributors_2024": "3",
-    "contributors_2023": "0"
+    "contributors_all": 19,
+    "contributors_2025": 16,
+    "contributors_2024": 3,
+    "contributors_2023": 0
   },
   {
     "repo_name": "SWE-bench",
@@ -52,10 +52,10 @@
     "github_about_section": "SWE-bench: Can Language Models Resolve Real-world Github Issues?",
     "homepage_link": "https://swebench.com",
     "github_topic_closest_fit": "benchmark",
-    "contributors_all": "66",
-    "contributors_2025": "33",
-    "contributors_2024": "37",
-    "contributors_2023": "9"
+    "contributors_all": 66,
+    "contributors_2025": 33,
+    "contributors_2024": 37,
+    "contributors_2023": 9
   },
   {
     "repo_name": "terminal-bench",
@@ -64,10 +64,10 @@
     "github_about_section": "A benchmark for LLMs on complicated tasks in the terminal",
     "homepage_link": "https://tbench.ai",
     "github_topic_closest_fit": "benchmark",
-    "contributors_all": "96",
-    "contributors_2025": "96",
-    "contributors_2024": "0",
-    "contributors_2023": "0"
+    "contributors_all": 96,
+    "contributors_2025": 96,
+    "contributors_2024": 0,
+    "contributors_2023": 0
   },
   {
     "repo_name": "TritonBench",
@@ -76,10 +76,10 @@
     "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",
-    "contributors_all": "3",
-    "contributors_2025": "3",
-    "contributors_2024": "0",
-    "contributors_2023": "0"
+    "contributors_all": 3,
+    "contributors_2025": 3,
+    "contributors_2024": 0,
+    "contributors_2023": 0
   },
   {
     "repo_name": "BitBLAS",
@@ -87,10 +87,10 @@
     "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",
-    "contributors_all": "17",
-    "contributors_2025": "5",
-    "contributors_2024": "14",
-    "contributors_2023": "0"
+    "contributors_all": 17,
+    "contributors_2025": 5,
+    "contributors_2024": 14,
+    "contributors_2023": 0
   },
   {
     "repo_name": "hipBLAS",
@@ -98,10 +98,10 @@
     "category": "Basic Linear Algebra Subprograms (BLAS)",
     "github_about_section": "[DEPRECATED] Moved to ROCm/rocm-libraries repo",
     "github_topic_closest_fit": "matrix-multiplication",
-    "contributors_all": "72",
-    "contributors_2025": "21",
-    "contributors_2024": "24",
-    "contributors_2023": "14"
+    "contributors_all": 72,
+    "contributors_2025": 21,
+    "contributors_2024": 24,
+    "contributors_2023": 14
   },
   {
     "repo_name": "hipBLASLt",
@@ -110,20 +110,20 @@
     "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",
-    "contributors_all": "111",
-    "contributors_2025": "69",
-    "contributors_2024": "70",
-    "contributors_2023": "35"
+    "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",
-    "contributors_all": "93",
-    "contributors_2025": "32",
-    "contributors_2024": "32",
-    "contributors_2023": "24"
+    "contributors_all": 93,
+    "contributors_2025": 32,
+    "contributors_2024": 32,
+    "contributors_2023": 24
   },
   {
     "repo_name": "llvm-project",
@@ -132,30 +132,30 @@
     "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",
-    "contributors_all": "6680",
-    "contributors_2025": "2378",
-    "contributors_2024": "2130",
-    "contributors_2023": "1920"
+    "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",
-    "contributors_all": "430",
-    "contributors_2025": "36",
-    "contributors_2024": "32",
-    "contributors_2023": "55"
+    "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",
-    "contributors_all": "9",
-    "contributors_2025": "0",
-    "contributors_2024": "3",
-    "contributors_2023": "3"
+    "contributors_all": 9,
+    "contributors_2025": 0,
+    "contributors_2024": 3,
+    "contributors_2023": 3
   },
   {
     "repo_name": "CU2CL",
@@ -163,10 +163,10 @@
     "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",
-    "contributors_all": "3",
-    "contributors_2025": "0",
-    "contributors_2024": "0",
-    "contributors_2023": "0"
+    "contributors_all": 3,
+    "contributors_2025": 0,
+    "contributors_2024": 0,
+    "contributors_2023": 0
   },
   {
     "repo_name": "cuda-python",
@@ -174,10 +174,10 @@
     "github_about_section": "CUDA Python: Performance meets Productivity",
     "homepage_link": "https://nvidia.github.io/cuda-python",
     "github_topic_closest_fit": "parallel-programming",
-    "contributors_all": "48",
-    "contributors_2025": "41",
-    "contributors_2024": "12",
-    "contributors_2023": "1"
+    "contributors_all": 48,
+    "contributors_2025": 41,
+    "contributors_2024": 12,
+    "contributors_2023": 1
   },
   {
     "repo_name": "OpenCL-SDK",
@@ -185,10 +185,10 @@
     "github_about_section": "OpenCL SDK",
     "homepage_link": "https://khronos.org/opencl",
     "github_topic_closest_fit": "parallel-programming",
-    "contributors_all": "25",
-    "contributors_2025": "8",
-    "contributors_2024": "6",
-    "contributors_2023": "9"
+    "contributors_all": 25,
+    "contributors_2025": 8,
+    "contributors_2024": 6,
+    "contributors_2023": 9
   },
   {
     "repo_name": "pocl",
@@ -196,10 +196,10 @@
     "github_about_section": "pocl - Portable Computing Language",
     "homepage_link": "https://portablecl.org",
     "github_topic_closest_fit": "parallel-programming",
-    "contributors_all": "166",
-    "contributors_2025": "26",
-    "contributors_2024": "27",
-    "contributors_2023": "21"
+    "contributors_all": 166,
+    "contributors_2025": 26,
+    "contributors_2024": 27,
+    "contributors_2023": 21
   },
   {
     "repo_name": "SYCL-Docs",
@@ -207,10 +207,10 @@
     "github_about_section": "SYCL Open Source Specification",
     "homepage_link": "https://khronos.org/sycl",
     "github_topic_closest_fit": "parallel-programming",
-    "contributors_all": "67",
-    "contributors_2025": "13",
-    "contributors_2024": "20",
-    "contributors_2023": "27"
+    "contributors_all": 67,
+    "contributors_2025": 13,
+    "contributors_2024": 20,
+    "contributors_2023": 27
   },
   {
     "repo_name": "triSYCL",
@@ -218,10 +218,10 @@
     "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",
-    "contributors_all": "31",
-    "contributors_2025": "0",
-    "contributors_2024": "1",
-    "contributors_2023": "3"
+    "contributors_all": 31,
+    "contributors_2025": 0,
+    "contributors_2024": 1,
+    "contributors_2023": 3
   },
   {
     "repo_name": "ZLUDA",
@@ -229,10 +229,10 @@
     "github_about_section": "CUDA on non-NVIDIA GPUs",
     "homepage_link": "https://vosen.github.io/ZLUDA",
     "github_topic_closest_fit": "parallel-programming",
-    "contributors_all": "15",
-    "contributors_2025": "8",
-    "contributors_2024": "4",
-    "contributors_2023": "0"
+    "contributors_all": 15,
+    "contributors_2025": 8,
+    "contributors_2024": 4,
+    "contributors_2023": 0
   },
   {
     "repo_name": "llama.cpp",
@@ -241,10 +241,10 @@
     "github_about_section": "LLM inference in C/C++",
     "homepage_link": "https://ggml.ai",
     "github_topic_closest_fit": "inference",
-    "contributors_all": "1374",
-    "contributors_2025": "535",
-    "contributors_2024": "575",
-    "contributors_2023": "461"
+    "contributors_all": 1374,
+    "contributors_2025": 535,
+    "contributors_2024": 575,
+    "contributors_2023": 461
   },
   {
     "repo_name": "mistral-inference",
@@ -253,10 +253,10 @@
     "github_about_section": "Official inference library for Mistral models",
     "homepage_link": "https://mistral.ai",
     "github_topic_closest_fit": "inference",
-    "contributors_all": "29",
-    "contributors_2025": "2",
-    "contributors_2024": "17",
-    "contributors_2023": "14"
+    "contributors_all": 29,
+    "contributors_2025": 2,
+    "contributors_2024": 17,
+    "contributors_2023": 14
   },
   {
     "repo_name": "ollama",
@@ -265,10 +265,10 @@
     "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",
-    "contributors_all": "574",
-    "contributors_2025": "202",
-    "contributors_2024": "314",
-    "contributors_2023": "97"
+    "contributors_all": 574,
+    "contributors_2025": 202,
+    "contributors_2024": 314,
+    "contributors_2023": 97
   },
   {
     "repo_name": "sglang",
@@ -277,20 +277,20 @@
     "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",
-    "contributors_all": "937",
-    "contributors_2025": "796",
-    "contributors_2024": "189",
-    "contributors_2023": "1"
+    "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",
-    "contributors_all": "104",
-    "contributors_2025": "10",
-    "contributors_2024": "18",
-    "contributors_2023": "19"
+    "contributors_all": 104,
+    "contributors_2025": 10,
+    "contributors_2024": 18,
+    "contributors_2023": 19
   },
   {
     "repo_name": "vllm",
@@ -299,20 +299,20 @@
     "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",
-    "contributors_all": "1885",
-    "contributors_2025": "1369",
-    "contributors_2024": "579",
-    "contributors_2023": "145"
+    "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",
-    "contributors_all": "15",
-    "contributors_2025": "14",
-    "contributors_2024": "2",
-    "contributors_2023": "0"
+    "contributors_all": 15,
+    "contributors_2025": 14,
+    "contributors_2024": 2,
+    "contributors_2023": 0
   },
   {
     "repo_name": "kernels-community",
@@ -320,10 +320,10 @@
     "category": "gpu kernels",
     "homepage_link": "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"
+    "contributors_all": 9,
+    "contributors_2025": 9,
+    "contributors_2024": 0,
+    "contributors_2023": 0
   },
   {
     "repo_name": "Liger-Kernel",
@@ -332,20 +332,20 @@
     "github_about_section": "Efficient Triton Kernels for LLM Training",
     "homepage_link": "https://openreview.net/pdf?id=36SjAIT42G",
     "github_topic_closest_fit": "triton",
-    "contributors_all": "120",
-    "contributors_2025": "78",
-    "contributors_2024": "61",
-    "contributors_2023": "0"
+    "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",
-    "contributors_all": "17",
-    "contributors_2025": "17",
-    "contributors_2024": "0",
-    "contributors_2023": "0"
+    "contributors_all": 17,
+    "contributors_2025": 17,
+    "contributors_2024": 0,
+    "contributors_2023": 0
   },
   {
     "repo_name": "reference-kernels",
@@ -353,10 +353,10 @@
     "category": "kernel examples",
     "github_about_section": "Official Problem Sets / Reference Kernels for the GPU MODE Leaderboard!",
     "homepage_link": "https://gpumode.com",
-    "contributors_all": "16",
-    "contributors_2025": "16",
-    "contributors_2024": "0",
-    "contributors_2023": "0"
+    "contributors_all": 16,
+    "contributors_2025": 16,
+    "contributors_2024": 0,
+    "contributors_2023": 0
   },
   {
     "repo_name": "pytorch",
@@ -365,10 +365,10 @@
     "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",
-    "contributors_all": "5434",
-    "contributors_2025": "1187",
-    "contributors_2024": "1090",
-    "contributors_2023": "1024"
+    "contributors_all": 5434,
+    "contributors_2025": 1187,
+    "contributors_2024": 1090,
+    "contributors_2023": 1024
   },
   {
     "repo_name": "tensorflow",
@@ -377,20 +377,20 @@
     "github_about_section": "An Open Source Machine Learning Framework for Everyone",
     "homepage_link": "https://tensorflow.org",
     "github_topic_closest_fit": "machine-learning",
-    "contributors_all": "4618",
-    "contributors_2025": "500",
-    "contributors_2024": "523",
-    "contributors_2023": "630"
+    "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",
-    "contributors_all": "2",
-    "contributors_2025": "1",
-    "contributors_2024": "1",
-    "contributors_2023": "0"
+    "contributors_all": 2,
+    "contributors_2025": 1,
+    "contributors_2024": 1,
+    "contributors_2023": 0
   },
   {
     "repo_name": "onnx",
@@ -399,10 +399,10 @@
     "github_about_section": "Open standard for machine learning interoperability",
     "homepage_link": "https://onnx.ai",
     "github_topic_closest_fit": "onnx",
-    "contributors_all": "370",
-    "contributors_2025": "56",
-    "contributors_2024": "45",
-    "contributors_2023": "61"
+    "contributors_all": 370,
+    "contributors_2025": 56,
+    "contributors_2024": 45,
+    "contributors_2023": 61
   },
   {
     "repo_name": "executorch",
@@ -410,10 +410,10 @@
     "category": "model compiler",
     "github_about_section": "On-device AI across mobile, embedded and edge for PyTorch",
     "homepage_link": "https://executorch.ai",
-    "contributors_all": "437",
-    "contributors_2025": "267",
-    "contributors_2024": "243",
-    "contributors_2023": "77"
+    "contributors_all": 437,
+    "contributors_2025": 267,
+    "contributors_2024": 243,
+    "contributors_2023": 77
   },
   {
     "repo_name": "cutlass",
@@ -422,10 +422,10 @@
     "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",
-    "contributors_all": "238",
-    "contributors_2025": "94",
-    "contributors_2024": "64",
-    "contributors_2023": "66"
+    "contributors_all": 238,
+    "contributors_2025": 94,
+    "contributors_2024": 64,
+    "contributors_2023": 66
   },
   {
     "repo_name": "ThunderKittens",
@@ -434,10 +434,10 @@
     "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",
-    "contributors_all": "34",
-    "contributors_2025": "29",
-    "contributors_2024": "13",
-    "contributors_2023": "0"
+    "contributors_all": 34,
+    "contributors_2025": 29,
+    "contributors_2024": 13,
+    "contributors_2023": 0
   },
   {
     "repo_name": "helion",
@@ -446,10 +446,10 @@
     "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",
-    "contributors_all": "49",
-    "contributors_2025": "49",
-    "contributors_2024": "0",
-    "contributors_2023": "0"
+    "contributors_all": 49,
+    "contributors_2025": 49,
+    "contributors_2024": 0,
+    "contributors_2023": 0
   },
   {
     "repo_name": "TileIR",
@@ -457,10 +457,10 @@
     "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",
-    "contributors_all": "10",
-    "contributors_2025": "10",
-    "contributors_2024": "1",
-    "contributors_2023": "0"
+    "contributors_all": 10,
+    "contributors_2025": 10,
+    "contributors_2024": 1,
+    "contributors_2023": 0
   },
   {
     "repo_name": "tilelang",
@@ -469,10 +469,10 @@
     "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",
-    "contributors_all": "90",
-    "contributors_2025": "89",
-    "contributors_2024": "1",
-    "contributors_2023": "0"
+    "contributors_all": 90,
+    "contributors_2025": 89,
+    "contributors_2024": 1,
+    "contributors_2023": 0
   },
   {
     "repo_name": "triton",
@@ -481,10 +481,10 @@
     "github_about_section": "Development repository for the Triton language and compiler",
     "homepage_link": "https://triton-lang.org",
     "github_topic_closest_fit": "parallel-programming",
-    "contributors_all": "522",
-    "contributors_2025": "233",
-    "contributors_2024": "206",
-    "contributors_2023": "159"
+    "contributors_all": 522,
+    "contributors_2025": 233,
+    "contributors_2024": 206,
+    "contributors_2023": 159
   },
   {
     "repo_name": "cupti",
@@ -492,10 +492,10 @@
     "category": "performance testing",
     "github_about_section": "Profile how CUDA applications create and modify data in memory.",
     "github_topic_closest_fit": "profiling",
-    "contributors_all": "1",
-    "contributors_2025": "0",
-    "contributors_2024": "0",
-    "contributors_2023": "0"
+    "contributors_all": 1,
+    "contributors_2025": 0,
+    "contributors_2024": 0,
+    "contributors_2023": 0
   },
   {
     "repo_name": "hatchet",
@@ -504,10 +504,10 @@
     "github_about_section": "Graph-indexed Pandas DataFrames for analyzing hierarchical performance data",
     "homepage_link": "https://llnl-hatchet.readthedocs.io",
     "github_topic_closest_fit": "profiling",
-    "contributors_all": "25",
-    "contributors_2025": "3",
-    "contributors_2024": "6",
-    "contributors_2023": "8"
+    "contributors_all": 25,
+    "contributors_2025": 3,
+    "contributors_2024": 6,
+    "contributors_2023": 8
   },
   {
     "repo_name": "intelliperf",
@@ -516,10 +516,10 @@
     "github_about_section": "Automated bottleneck detection and solution orchestration",
     "homepage_link": "https://arxiv.org/html/2508.20258v1",
     "github_topic_closest_fit": "profiling",
-    "contributors_all": "7",
-    "contributors_2025": "7",
-    "contributors_2024": "0",
-    "contributors_2023": "0"
+    "contributors_all": 7,
+    "contributors_2025": 7,
+    "contributors_2024": 0,
+    "contributors_2023": 0
   },
   {
     "repo_name": "omnitrace",
@@ -528,10 +528,10 @@
     "github_about_section": "Omnitrace: Application Profiling, Tracing, and Analysis",
     "homepage_link": "https://rocm.docs.amd.com/projects/omnitrace",
     "github_topic_closest_fit": "profiling",
-    "contributors_all": "16",
-    "contributors_2025": "2",
-    "contributors_2024": "12",
-    "contributors_2023": "2"
+    "contributors_all": 16,
+    "contributors_2025": 2,
+    "contributors_2024": 12,
+    "contributors_2023": 2
   },
   {
     "repo_name": "jax",
@@ -540,10 +540,10 @@
     "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",
-    "contributors_all": "997",
-    "contributors_2025": "312",
-    "contributors_2024": "280",
-    "contributors_2023": "202"
+    "contributors_all": 997,
+    "contributors_2025": 312,
+    "contributors_2024": 280,
+    "contributors_2023": 202
   },
   {
     "repo_name": "numpy",
@@ -552,10 +552,10 @@
     "github_about_section": "The fundamental package for scientific computing with Python.",
     "homepage_link": "https://numpy.org",
     "github_topic_closest_fit": "scientific-computing",
-    "contributors_all": "2172",
-    "contributors_2025": "235",
-    "contributors_2024": "233",
-    "contributors_2023": "252"
+    "contributors_all": 2172,
+    "contributors_2025": 235,
+    "contributors_2024": 233,
+    "contributors_2023": 252
   },
   {
     "repo_name": "scipy",
@@ -564,10 +564,10 @@
     "github_about_section": "SciPy library main repository",
     "homepage_link": "https://scipy.org",
     "github_topic_closest_fit": "scientific-computing",
-    "contributors_all": "1973",
-    "contributors_2025": "210",
-    "contributors_2024": "251",
-    "contributors_2023": "245"
+    "contributors_all": 1973,
+    "contributors_2025": 210,
+    "contributors_2024": 251,
+    "contributors_2023": 245
   },
   {
     "repo_name": "elasticsearch",
@@ -576,10 +576,10 @@
     "github_about_section": "Free and Open Source, Distributed, RESTful Search Engine",
     "homepage_link": "https://elastic.co/products/elasticsearch",
     "github_topic_closest_fit": "search-engine",
-    "contributors_all": "2297",
-    "contributors_2025": "316",
-    "contributors_2024": "284",
-    "contributors_2023": "270"
+    "contributors_all": 2297,
+    "contributors_2025": 316,
+    "contributors_2024": 284,
+    "contributors_2023": 270
   },
   {
     "repo_name": "jupyterlab",
@@ -588,10 +588,10 @@
     "github_about_section": "JupyterLab computational environment.",
     "homepage_link": "https://jupyterlab.readthedocs.io",
     "github_topic_closest_fit": "jupyter",
-    "contributors_all": "698",
-    "contributors_2025": "77",
-    "contributors_2024": "85",
-    "contributors_2023": "100"
+    "contributors_all": 698,
+    "contributors_2025": 77,
+    "contributors_2024": 85,
+    "contributors_2023": 100
   },
   {
     "repo_name": "milvus",
@@ -600,30 +600,30 @@
     "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",
-    "contributors_all": "387",
-    "contributors_2025": "95",
-    "contributors_2024": "84",
-    "contributors_2023": "72"
+    "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",
-    "contributors_all": "392",
-    "contributors_2025": "97",
-    "contributors_2024": "124",
-    "contributors_2023": "149"
+    "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",
-    "contributors_all": "151",
-    "contributors_2025": "145",
-    "contributors_2024": "10",
-    "contributors_2023": "0"
+    "contributors_all": 151,
+    "contributors_2025": 145,
+    "contributors_2024": 10,
+    "contributors_2023": 0
   },
   {
     "repo_name": "ao",
@@ -631,30 +631,30 @@
     "github_about_section": "PyTorch native quantization and sparsity for training and inference",
     "homepage_link": "https://pytorch.org/ao",
     "github_topic_closest_fit": "quantization",
-    "contributors_all": "178",
-    "contributors_2025": "114",
-    "contributors_2024": "100",
-    "contributors_2023": "5"
+    "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",
-    "contributors_all": "237",
-    "contributors_2025": "99",
-    "contributors_2024": "104",
-    "contributors_2023": "62"
+    "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",
-    "contributors_all": "218",
-    "contributors_2025": "20",
-    "contributors_2024": "28",
-    "contributors_2023": "22"
+    "contributors_all": 218,
+    "contributors_2025": 20,
+    "contributors_2024": 28,
+    "contributors_2023": 22
   },
   {
     "repo_name": "ComfyUI",
@@ -663,10 +663,10 @@
     "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",
-    "contributors_all": "278",
-    "contributors_2025": "108",
-    "contributors_2024": "119",
-    "contributors_2023": "94"
+    "contributors_all": 278,
+    "contributors_2025": 108,
+    "contributors_2024": 119,
+    "contributors_2023": 94
   },
   {
     "repo_name": "composable_kernel",
@@ -674,10 +674,10 @@
     "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",
-    "contributors_all": "190",
-    "contributors_2025": "140",
-    "contributors_2024": "58",
-    "contributors_2023": "33"
+    "contributors_all": 190,
+    "contributors_2025": 140,
+    "contributors_2024": 58,
+    "contributors_2023": 33
   },
   {
     "repo_name": "cudnn-frontend",
@@ -686,10 +686,10 @@
     "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",
-    "contributors_all": "12",
-    "contributors_2025": "6",
-    "contributors_2024": "5",
-    "contributors_2023": "1"
+    "contributors_all": 12,
+    "contributors_2025": 6,
+    "contributors_2024": 5,
+    "contributors_2023": 1
   },
   {
     "repo_name": "cuJSON",
@@ -698,20 +698,20 @@
     "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",
-    "contributors_all": "2",
-    "contributors_2025": "2",
-    "contributors_2024": "2",
-    "contributors_2023": "0"
+    "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",
-    "contributors_all": "442",
-    "contributors_2025": "96",
-    "contributors_2024": "134",
-    "contributors_2023": "165"
+    "contributors_all": 442,
+    "contributors_2025": 96,
+    "contributors_2024": 134,
+    "contributors_2023": 165
   },
   {
     "repo_name": "dstack",
@@ -720,10 +720,10 @@
     "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",
-    "contributors_all": "69",
-    "contributors_2025": "28",
-    "contributors_2024": "42",
-    "contributors_2023": "14"
+    "contributors_all": 69,
+    "contributors_2025": 28,
+    "contributors_2024": 42,
+    "contributors_2023": 14
   },
   {
     "repo_name": "flashinfer",
@@ -732,10 +732,10 @@
     "github_about_section": "FlashInfer: Kernel Library for LLM Serving",
     "homepage_link": "https://flashinfer.ai",
     "github_topic_closest_fit": "attention",
-    "contributors_all": "205",
-    "contributors_2025": "158",
-    "contributors_2024": "50",
-    "contributors_2023": "11"
+    "contributors_all": 205,
+    "contributors_2025": 158,
+    "contributors_2024": 50,
+    "contributors_2023": 11
   },
   {
     "repo_name": "FTorch",
@@ -744,10 +744,10 @@
     "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",
-    "contributors_all": "20",
-    "contributors_2025": "11",
-    "contributors_2024": "8",
-    "contributors_2023": "9"
+    "contributors_all": 20,
+    "contributors_2025": 11,
+    "contributors_2024": 8,
+    "contributors_2023": 9
   },
   {
     "repo_name": "GEAK-agent",
@@ -755,40 +755,40 @@
     "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",
-    "contributors_all": "9",
-    "contributors_2025": "9",
-    "contributors_2024": "0",
-    "contributors_2023": "0"
+    "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",
-    "contributors_all": "2624",
-    "contributors_2025": "692",
-    "contributors_2024": "648",
-    "contributors_2023": "604"
+    "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",
-    "contributors_all": "288",
-    "contributors_2025": "46",
-    "contributors_2024": "31",
-    "contributors_2023": "25"
+    "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",
-    "contributors_all": "54",
-    "contributors_2025": "10",
-    "contributors_2024": "19",
-    "contributors_2023": "13"
+    "contributors_all": 54,
+    "contributors_2025": 10,
+    "contributors_2024": 19,
+    "contributors_2023": 13
   },
   {
     "repo_name": "IMO2025",
@@ -797,10 +797,10 @@
     "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",
-    "contributors_all": "2",
-    "contributors_2025": "2",
-    "contributors_2024": "0",
-    "contributors_2023": "0"
+    "contributors_all": 2,
+    "contributors_2025": 2,
+    "contributors_2024": 0,
+    "contributors_2023": 0
   },
   {
     "repo_name": "kubernetes",
@@ -809,10 +809,10 @@
     "github_about_section": "Production-Grade Container Scheduling and Management",
     "homepage_link": "https://kubernetes.io",
     "github_topic_closest_fit": "kubernetes",
-    "contributors_all": "5041",
-    "contributors_2025": "509",
-    "contributors_2024": "498",
-    "contributors_2023": "565"
+    "contributors_all": 5041,
+    "contributors_2025": 509,
+    "contributors_2024": 498,
+    "contributors_2023": 565
   },
   {
     "repo_name": "lapack",
@@ -821,10 +821,10 @@
     "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",
-    "contributors_all": "178",
-    "contributors_2025": "20",
-    "contributors_2024": "24",
-    "contributors_2023": "42"
+    "contributors_all": 178,
+    "contributors_2025": 20,
+    "contributors_2024": 24,
+    "contributors_2023": 42
   },
   {
     "repo_name": "lean4",
@@ -833,10 +833,10 @@
     "github_about_section": "Lean 4 programming language and theorem prover",
     "homepage_link": "https://lean-lang.org",
     "github_topic_closest_fit": "lean",
-    "contributors_all": "278",
-    "contributors_2025": "110",
-    "contributors_2024": "85",
-    "contributors_2023": "64"
+    "contributors_all": 278,
+    "contributors_2025": 110,
+    "contributors_2024": 85,
+    "contributors_2023": 64
   },
   {
     "repo_name": "letta",
@@ -845,29 +845,29 @@
     "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",
-    "contributors_all": "157",
-    "contributors_2025": "56",
-    "contributors_2024": "75",
-    "contributors_2023": "47"
+    "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.",
-    "contributors_all": "76",
-    "contributors_2025": "44",
-    "contributors_2024": "47",
-    "contributors_2023": "29"
+    "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",
-    "contributors_all": "152",
-    "contributors_2025": "144",
-    "contributors_2024": "18",
-    "contributors_2023": "0"
+    "contributors_all": 152,
+    "contributors_2025": 144,
+    "contributors_2024": 18,
+    "contributors_2023": 0
   },
   {
     "repo_name": "mcp-agent",
@@ -875,30 +875,30 @@
     "category": "mcp",
     "github_about_section": "Build effective agents using Model Context Protocol and simple workflow patterns",
     "github_topic_closest_fit": "mcp",
-    "contributors_all": "63",
-    "contributors_2025": "63",
-    "contributors_2024": "1",
-    "contributors_2023": "0"
+    "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",
-    "contributors_all": "121",
-    "contributors_2025": "37",
-    "contributors_2024": "35",
-    "contributors_2023": "28"
+    "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",
-    "contributors_all": "204",
-    "contributors_2025": "47",
-    "contributors_2024": "62",
-    "contributors_2023": "44"
+    "contributors_all": 204,
+    "contributors_2025": 47,
+    "contributors_2024": 62,
+    "contributors_2023": 44
   },
   {
     "repo_name": "modelcontextprotocol",
@@ -907,10 +907,10 @@
     "github_about_section": "Specification and documentation for the Model Context Protocol",
     "homepage_link": "https://modelcontextprotocol.io",
     "github_topic_closest_fit": "mcp",
-    "contributors_all": "327",
-    "contributors_2025": "298",
-    "contributors_2024": "42",
-    "contributors_2023": "0"
+    "contributors_all": 327,
+    "contributors_2025": 298,
+    "contributors_2024": 42,
+    "contributors_2023": 0
   },
   {
     "repo_name": "modular",
@@ -919,20 +919,20 @@
     "github_about_section": "The Modular Platform (includes MAX & Mojo)",
     "homepage_link": "https://docs.modular.com",
     "github_topic_closest_fit": "parallel-programming",
-    "contributors_all": "366",
-    "contributors_2025": "222",
-    "contributors_2024": "205",
-    "contributors_2023": "99"
+    "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",
-    "contributors_all": "85",
-    "contributors_2025": "85",
-    "contributors_2024": "0",
-    "contributors_2023": "0"
+    "contributors_all": 85,
+    "contributors_2025": 85,
+    "contributors_2024": 0,
+    "contributors_2023": 0
   },
   {
     "repo_name": "Mooncake",
@@ -940,37 +940,37 @@
     "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",
-    "contributors_all": "138",
-    "contributors_2025": "133",
-    "contributors_2024": "13",
-    "contributors_2023": "0"
+    "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",
-    "contributors_all": "51",
-    "contributors_2025": "7",
-    "contributors_2024": "5",
-    "contributors_2023": "6"
+    "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",
-    "contributors_all": "11",
-    "contributors_2025": "9",
-    "contributors_2024": "3",
-    "contributors_2023": "0"
+    "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)",
-    "contributors_all": "78",
-    "contributors_2025": "78",
-    "contributors_2024": "0",
-    "contributors_2023": "0"
+    "contributors_all": 78,
+    "contributors_2025": 78,
+    "contributors_2024": 0,
+    "contributors_2023": 0
   },
   {
     "repo_name": "ome",
@@ -978,10 +978,10 @@
     "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",
-    "contributors_all": "28",
-    "contributors_2025": "28",
-    "contributors_2024": "0",
-    "contributors_2023": "0"
+    "contributors_all": 28,
+    "contributors_2025": 28,
+    "contributors_2024": 0,
+    "contributors_2023": 0
   },
   {
     "repo_name": "ondemand",
@@ -989,39 +989,39 @@
     "github_about_section": "Supercomputing. Seamlessly. Open, Interactive HPC Via the Web",
     "homepage_link": "https://openondemand.org",
     "github_topic_closest_fit": "hpc",
-    "contributors_all": "117",
-    "contributors_2025": "43",
-    "contributors_2024": "23",
-    "contributors_2023": "21"
+    "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",
-    "contributors_all": "67",
-    "contributors_2025": "17",
-    "contributors_2024": "29",
-    "contributors_2023": "28"
+    "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",
-    "contributors_all": "46",
-    "contributors_2025": "46",
-    "contributors_2024": "0",
-    "contributors_2023": "0"
+    "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",
-    "contributors_all": "47",
-    "contributors_2025": "0",
-    "contributors_2024": "7",
-    "contributors_2023": "9"
+    "contributors_all": 47,
+    "contributors_2025": 0,
+    "contributors_2024": 7,
+    "contributors_2023": 9
   },
   {
     "repo_name": "peft",
@@ -1029,18 +1029,18 @@
     "github_about_section": "PEFT: State-of-the-art Parameter-Efficient Fine-Tuning.",
     "homepage_link": "https://huggingface.co/docs/peft",
     "github_topic_closest_fit": "lora",
-    "contributors_all": "272",
-    "contributors_2025": "69",
-    "contributors_2024": "111",
-    "contributors_2023": "115"
+    "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",
-    "contributors_all": "12",
-    "contributors_2025": "12",
-    "contributors_2024": "0",
-    "contributors_2023": "0"
+    "contributors_all": 12,
+    "contributors_2025": 12,
+    "contributors_2024": 0,
+    "contributors_2023": 0
   },
   {
     "repo_name": "pybind11",
@@ -1048,10 +1048,10 @@
     "github_about_section": "Seamless operability between C++11 and Python",
     "homepage_link": "https://pybind11.readthedocs.io",
     "github_topic_closest_fit": "bindings",
-    "contributors_all": "404",
-    "contributors_2025": "43",
-    "contributors_2024": "45",
-    "contributors_2023": "42"
+    "contributors_all": 404,
+    "contributors_2025": 43,
+    "contributors_2024": 45,
+    "contributors_2023": 42
   },
   {
     "repo_name": "RaBitQ",
@@ -1059,98 +1059,98 @@
     "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",
-    "contributors_all": "2",
-    "contributors_2025": "2",
-    "contributors_2024": "1",
-    "contributors_2023": "0"
+    "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",
-    "contributors_all": "437",
-    "contributors_2025": "58",
-    "contributors_2024": "61",
-    "contributors_2023": "66"
+    "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",
-    "contributors_all": "81",
-    "contributors_2025": "17",
-    "contributors_2024": "20",
-    "contributors_2023": "19"
+    "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",
-    "contributors_all": "166",
-    "contributors_2025": "67",
-    "contributors_2024": "61",
-    "contributors_2023": "44"
+    "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",
-    "contributors_all": "1032",
-    "contributors_2025": "440",
-    "contributors_2024": "323",
-    "contributors_2023": "204"
+    "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",
-    "contributors_all": "76",
-    "contributors_2025": "12",
-    "contributors_2024": "28",
-    "contributors_2023": "15"
+    "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",
-    "contributors_all": "85",
-    "contributors_2025": "10",
-    "contributors_2024": "32",
-    "contributors_2023": "26"
+    "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",
-    "contributors_all": "59",
-    "contributors_2025": "20",
-    "contributors_2024": "23",
-    "contributors_2023": "15"
+    "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",
-    "contributors_all": "65",
-    "contributors_2025": "19",
-    "contributors_2024": "24",
-    "contributors_2023": "18"
+    "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",
-    "contributors_all": "45",
-    "contributors_2025": "8",
-    "contributors_2024": "11",
-    "contributors_2023": "6"
+    "contributors_all": 45,
+    "contributors_2025": 8,
+    "contributors_2024": 11,
+    "contributors_2023": 6
   },
   {
     "repo_name": "Self-Forcing",
@@ -1159,10 +1159,10 @@
     "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",
-    "contributors_all": "4",
-    "contributors_2025": "4",
-    "contributors_2024": "0",
-    "contributors_2023": "0"
+    "contributors_all": 4,
+    "contributors_2025": 4,
+    "contributors_2024": 0,
+    "contributors_2023": 0
   },
   {
     "repo_name": "server",
@@ -1170,10 +1170,10 @@
     "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",
-    "contributors_all": "147",
-    "contributors_2025": "24",
-    "contributors_2024": "36",
-    "contributors_2023": "34"
+    "contributors_all": 147,
+    "contributors_2025": 24,
+    "contributors_2024": 36,
+    "contributors_2023": 34
   },
   {
     "repo_name": "spark",
@@ -1181,10 +1181,10 @@
     "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",
-    "contributors_all": "3083",
-    "contributors_2025": "322",
-    "contributors_2024": "300",
-    "contributors_2023": "336"
+    "contributors_all": 3083,
+    "contributors_2025": 322,
+    "contributors_2024": 300,
+    "contributors_2023": 336
   },
   {
     "repo_name": "StreamDiffusion",
@@ -1193,10 +1193,10 @@
     "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",
-    "contributors_all": "29",
-    "contributors_2025": "0",
-    "contributors_2024": "9",
-    "contributors_2023": "25"
+    "contributors_all": 29,
+    "contributors_2025": 0,
+    "contributors_2024": 9,
+    "contributors_2023": 25
   },
   {
     "repo_name": "streamv2v",
@@ -1205,10 +1205,10 @@
     "github_about_section": "Official Pytorch implementation of StreamV2V.",
     "homepage_link": "https://jeff-liangf.github.io/projects/streamv2v",
     "github_topic_closest_fit": "diffusion-models",
-    "contributors_all": "7",
-    "contributors_2025": "3",
-    "contributors_2024": "6",
-    "contributors_2023": "0"
+    "contributors_all": 7,
+    "contributors_2025": 3,
+    "contributors_2024": 6,
+    "contributors_2023": 0
   },
   {
     "repo_name": "synthetic-data-kit",
@@ -1217,97 +1217,97 @@
     "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",
-    "contributors_all": "15",
-    "contributors_2025": "15",
-    "contributors_2024": "0",
-    "contributors_2023": "0"
+    "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",
-    "contributors_all": "137",
-    "contributors_2025": "16",
-    "contributors_2024": "25",
-    "contributors_2023": "22"
+    "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).",
-    "contributors_all": "111",
-    "contributors_2025": "19",
-    "contributors_2024": "25",
-    "contributors_2023": "31"
+    "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.",
-    "contributors_all": "63",
-    "contributors_2025": "0",
-    "contributors_2024": "1",
-    "contributors_2023": "4"
+    "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",
-    "contributors_all": "145",
-    "contributors_2025": "119",
-    "contributors_2024": "43",
-    "contributors_2023": "1"
+    "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",
-    "contributors_all": "3582",
-    "contributors_2025": "860",
-    "contributors_2024": "769",
-    "contributors_2023": "758"
+    "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",
-    "contributors_all": "30",
-    "contributors_2025": "30",
-    "contributors_2024": "0",
-    "contributors_2023": "0"
+    "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",
-    "contributors_all": "1",
-    "contributors_2025": "1",
-    "contributors_2024": "0",
-    "contributors_2023": "0"
+    "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",
-    "contributors_all": "15",
-    "contributors_2025": "15",
-    "contributors_2024": "0",
-    "contributors_2023": "0"
+    "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",
-    "contributors_all": "433",
-    "contributors_2025": "189",
-    "contributors_2024": "154",
-    "contributors_2023": "122"
+    "contributors_all": 433,
+    "contributors_2025": 189,
+    "contributors_2024": 154,
+    "contributors_2023": 122
   },
   {
     "repo_name": "truss",
@@ -1316,10 +1316,10 @@
     "github_about_section": "The simplest way to serve AI/ML models in production",
     "homepage_link": "https://truss.baseten.co",
     "github_topic_closest_fit": "inference",
-    "contributors_all": "72",
-    "contributors_2025": "44",
-    "contributors_2024": "30",
-    "contributors_2023": "21"
+    "contributors_all": 72,
+    "contributors_2025": 44,
+    "contributors_2024": 30,
+    "contributors_2023": 21
   },
   {
     "repo_name": "unsloth",
@@ -1328,10 +1328,10 @@
     "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",
-    "contributors_all": "127",
-    "contributors_2025": "102",
-    "contributors_2024": "27",
-    "contributors_2023": "3"
+    "contributors_all": 127,
+    "contributors_2025": 102,
+    "contributors_2024": 27,
+    "contributors_2023": 3
   },
   {
     "repo_name": "verl",
@@ -1340,10 +1340,10 @@
     "github_about_section": "verl: Volcano Engine Reinforcement Learning for LLMs",
     "homepage_link": "https://verl.readthedocs.io",
     "github_topic_closest_fit": "deep-reinforcement-learning",
-    "contributors_all": "462",
-    "contributors_2025": "454",
-    "contributors_2024": "10",
-    "contributors_2023": "0"
+    "contributors_all": 462,
+    "contributors_2025": 454,
+    "contributors_2024": 10,
+    "contributors_2023": 0
   },
   {
     "repo_name": "Vulkan-Hpp",
@@ -1352,10 +1352,10 @@
     "github_about_section": "Open-Source Vulkan C++ API",
     "homepage_link": "https://vulkan.org",
     "github_topic_closest_fit": "vulkan",
-    "contributors_all": "102",
-    "contributors_2025": "21",
-    "contributors_2024": "15",
-    "contributors_2023": "15"
+    "contributors_all": 102,
+    "contributors_2025": 21,
+    "contributors_2024": 15,
+    "contributors_2023": 15
   },
   {
     "repo_name": "Vulkan-Tools",
@@ -1364,10 +1364,10 @@
     "github_about_section": "Vulkan Development Tools",
     "homepage_link": "https://vulkan.org",
     "github_topic_closest_fit": "vulkan",
-    "contributors_all": "248",
-    "contributors_2025": "20",
-    "contributors_2024": "24",
-    "contributors_2023": "24"
+    "contributors_all": 248,
+    "contributors_2025": 20,
+    "contributors_2024": 24,
+    "contributors_2023": 24
   },
   {
     "repo_name": "Vulkan-Docs",
@@ -1376,10 +1376,10 @@
     "github_about_section": "The Vulkan API Specification and related tools",
     "homepage_link": "https://vulkan.org",
     "github_topic_closest_fit": "vulkan",
-    "contributors_all": "141",
-    "contributors_2025": "18",
-    "contributors_2024": "21",
-    "contributors_2023": "34"
+    "contributors_all": 141,
+    "contributors_2025": 18,
+    "contributors_2024": 21,
+    "contributors_2023": 34
   },
   {
     "repo_name": "Wan2.2",
@@ -1388,10 +1388,10 @@
     "github_about_section": "Wan: Open and Advanced Large-Scale Video Generative Models",
     "homepage_link": "https://wan.video",
     "github_topic_closest_fit": "diffusion-models",
-    "contributors_all": "14",
-    "contributors_2025": "14",
-    "contributors_2024": "0",
-    "contributors_2023": "0"
+    "contributors_all": 14,
+    "contributors_2025": 14,
+    "contributors_2024": 0,
+    "contributors_2023": 0
   },
   {
     "repo_name": "warp",
@@ -1400,9 +1400,9 @@
     "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",
-    "contributors_all": "79",
-    "contributors_2025": "40",
-    "contributors_2024": "29",
-    "contributors_2023": "17"
+    "contributors_all": 79,
+    "contributors_2025": 40,
+    "contributors_2024": 29,
+    "contributors_2023": 17
   }
 ]