Reorder to put similar projects close to each other
Browse files- PyTorchConference2025_GithubRepos.json +374 -380
PyTorchConference2025_GithubRepos.json
CHANGED
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@@ -7,27 +7,6 @@
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"closest_github_tag": "machine-learning",
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"category": "machine learning framework"
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},
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{
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"github_repo_link": "https://github.com/ggml-org/llama.cpp",
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"repo_name": "llama.cpp",
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"repo_description": "LLM inference in C/C++",
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"closest_github_tag": "ggml",
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"category": "inference engine"
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"github_repo_link": "https://github.com/onnx/onnx",
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"repo_name": "onnx",
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"repo_description": "Open standard for machine learning interoperability",
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"homepage_link": "https://onnx.ai/",
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"closest_github_tag": "deep-learning"
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"github_repo_link": "https://github.com/ray-project/ray",
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"repo_name": "ray",
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"repo_description": "Ray is an AI compute engine. Ray consists of a core distributed runtime and a set of AI Libraries for accelerating ML workloads.",
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"homepage_link": "https://ray.io",
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"closest_github_tag": "deep-learning"
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"github_repo_link": "https://github.com/vllm-project/vllm",
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"repo_name": "vllm",
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"category": "inference engine"
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{
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"github_repo_link": "https://github.com/
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"github_repo_link": "https://github.com/pytorch/ao",
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"repo_name": "ao",
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"repo_description": "PyTorch native quantization and sparsity for training and inference",
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"homepage_link": "https://pytorch.org/ao/stable/index.html",
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"closest_github_tag": "quantization"
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{
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"github_repo_link": "https://github.com/triton-lang/triton",
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"homepage_link": "https://triton-lang.org/",
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"category": "dsl"
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{
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"github_repo_link": "https://github.com/HazyResearch/ThunderKittens",
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"repo_name": "ThunderKittens",
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"repo_description": "Tile primitives for speedy kernels"
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{
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"github_repo_link": "https://github.com/gpu-mode/reference-kernels",
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"repo_name": "reference-kernels",
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"repo_description": "Official Problem Sets / Reference Kernels for the GPU MODE Leaderboard!",
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"homepage_link": "https://gpumode.com",
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"closest_github_tag": "gpu",
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"category": "kernels"
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"github_repo_link": "https://github.com/pytorch/executorch",
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"repo_name": "executorch",
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"category": "model compiler"
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{
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"github_repo_link": "https://github.com/
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"github_repo_link": "https://github.com/
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"github_repo_link": "https://github.com/
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"homepage_link": "https://
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"closest_github_tag": "
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{
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"github_repo_link": "https://github.com/
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"github_repo_link": "https://github.com/letta-ai/letta",
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@@ -126,59 +186,108 @@
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"closest_github_tag": "ai-agents"
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{
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"github_repo_link": "https://github.com/
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"closest_github_tag": "jupyter",
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"category": "ui"
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"github_repo_link": "https://github.com/
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"category": "machine learning framework"
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"github_repo_link": "https://github.com/ROCm/ROCm",
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"closest_github_tag": "documentation"
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{
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"github_repo_link": "https://github.com/cwpearson/cupti",
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"homepage_link": "https://triton-distributed.readthedocs.io/en/latest/",
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"category": "model compiler"
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"github_repo_link": "https://github.com/linkedin/Liger-Kernel",
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"repo_name": "Liger-Kernel",
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"repo_description": "Efficient Triton Kernels for LLM Training",
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"homepage_link": "https://openreview.net/pdf?id=36SjAIT42G",
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"closest_github_tag": "triton",
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"category": "kernels"
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"github_repo_link": "https://github.com/thunlp/TritonBench",
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"repo_name": "TritonBench",
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"repo_description": "TritonBench: Benchmarking Large Language Model Capabilities for Generating Triton Operators",
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"category": "benchmark"
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"github_repo_link": "https://github.com/meta-pytorch/tritonparse",
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"repo_name": "tritonparse",
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"homepage_link": "https://meta-pytorch.org/tritonparse/",
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"closest_github_tag": "triton"
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"github_repo_link": "https://github.com/elastic/elasticsearch",
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"repo_name": "elasticsearch",
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"repo_description": "Specification and documentation for the Model Context Protocol",
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"homepage_link": "https://modelcontextprotocol.io"
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"repo_description": "Build effective agents using Model Context Protocol and simple workflow patterns",
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"github_repo_link": "https://github.com/milvus-io/milvus",
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"homepage_link": "https://dstack.ai",
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"github_repo_link": "https://github.com/sandialabs/torchdendrite",
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"closest_github_tag": "scr-3078",
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"category": "machine learning framework"
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"repo_description": "PyTorch compiler that accelerates training and inference. Get built-in optimizations for performance, memory, parallelism, and easily write your own."
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"repo_description": "A Python-level JIT compiler designed to make unmodified PyTorch programs faster."
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"github_repo_link": "https://github.com/pytorch/torchtitan",
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"repo_name": "torchtitan",
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"repo_name": "ort",
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"repo_description": "Accelerate PyTorch models with ONNX Runtime"
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"homepage_link": "https://docs.nvidia.com/deeplearning/nccl/user-guide/docs/index.html",
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"github_repo_link": "https://github.com/sgl-project/ome",
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"homepage_link": "http://docs.sglang.ai/ome/",
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"closest_github_tag": "k8s"
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"repo_description": "RDMA core userspace libraries and daemons",
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"repo_description": "AI Tensor Engine for ROCm"
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"repo_description": "KernelBench: Can LLMs Write GPU Kernels? - Benchmark with Torch -> CUDA problems",
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"homepage_link": "https://scalingintelligence.stanford.edu/blogs/kernelbench/",
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"repo_description": "TritonBench: Benchmarking Large Language Model Capabilities for Generating Triton Operators",
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"github_repo_link": "https://github.com/AutomataLab/cuJSON",
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"repo_name": "cuJSON",
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"repo_description": "A benchmark for LLMs on complicated tasks in the terminal",
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"github_repo_link": "https://github.com/block/goose",
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"repo_name": "goose",
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"repo_description": "an open source, extensible AI agent that goes beyond code suggestions - install, execute, edit, and test with any LLM",
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"homepage_link": "https://block.github.io/goose/",
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"github_repo_link": "https://github.com/kvcache-ai/Mooncake",
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"repo_name": "Mooncake",
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"homepage_link": "https://kvcache-ai.github.io/Mooncake/",
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{
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"github_repo_link": "https://github.com/SWE-bench/SWE-bench",
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"repo_description": "SWE-bench: Can Language Models Resolve Real-world Github Issues?",
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"github_repo_link": "https://github.com/Dao-AILab/quack",
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"repo_name": "quack",
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"repo_description": "A Quirky Assortment of CuTe Kernels",
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{
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"github_repo_link": "https://github.com/KhronosGroup/SYCL-Docs",
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"repo_name": "SYCL-Docs",
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@@ -715,6 +710,66 @@
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"repo_description": "A plugin for Jupyter Notebook to run CUDA C/C++ code",
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{
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"github_repo_link": "https://github.com/ROCm/rocSOLVER",
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"repo_name": "rocSOLVER",
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@@ -767,66 +822,5 @@
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"repo_name": "MIOpen",
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"repo_description": "[DEPRECATED] Moved to ROCm/rocm-libraries repo",
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"homepage_link": "https://github.com/ROCm/rocm-libraries"
|
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"homepage_link": "https://ccache.dev",
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"repo_description": "Omnitrace: Application Profiling, Tracing, and Analysis",
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"homepage_link": "https://rocm.docs.amd.com/projects/omnitrace/en/docs-6.2.4/",
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{
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"repo_description": "Tool for generating high quality Synthetic datasets",
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"repo_description": "Fine-tuning & Reinforcement Learning for LLMs. 🦥 Train OpenAI gpt-oss, DeepSeek-R1, Qwen3, Gemma 3, TTS 2x faster with 70% less VRAM.",
|
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"homepage_link": "https://docs.unsloth.ai/",
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{
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"github_repo_link": "https://github.com/KhronosGroup/Vulkan-Docs",
|
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"repo_name": "Vulkan-Docs",
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"repo_description": "The Vulkan API Specification and related tools"
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"github_repo_link": "https://github.com/tensorflow/tflite-micro",
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"repo_description": "Infrastructure to enable deployment of ML models to low-power resource-constrained embedded targets (including microcontrollers and digital signal processors)."
|
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{
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"github_repo_link": "https://github.com/Wan-Video/Wan2.2",
|
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"repo_name": "Wan2.2",
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"repo_description": "Wan: Open and Advanced Large-Scale Video Generative Models",
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"homepage_link": "https://wan.video",
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"github_repo_link": "https://github.com/AMD-AGI/Primus-Turbo",
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"repo_name": "Primus-Turbo"
|
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}
|
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]
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"closest_github_tag": "machine-learning",
|
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"category": "machine learning framework"
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{
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"github_repo_link": "https://github.com/vllm-project/vllm",
|
| 12 |
"repo_name": "vllm",
|
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| 32 |
"category": "inference engine"
|
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},
|
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{
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+
"github_repo_link": "https://github.com/ggml-org/llama.cpp",
|
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| 399 |
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| 400 |
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| 401 |
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| 402 |
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| 403 |
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"repo_name": "nixl",
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| 404 |
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"repo_description": "NVIDIA Inference Xfer Library (NIXL)"
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| 405 |
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},
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| 406 |
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{
|
| 407 |
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|
| 408 |
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"repo_name": "Self-Forcing",
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| 409 |
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"repo_description": "Official codebase for \"Self Forcing: Bridging Training and Inference in Autoregressive Video Diffusion\" (NeurIPS 2025 Spotlight)",
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| 410 |
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| 411 |
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| 412 |
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| 413 |
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| 414 |
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"repo_name": "StreamDiffusion",
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| 415 |
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"repo_description": "StreamDiffusion: A Pipeline-Level Solution for Real-Time Interactive Generation"
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| 416 |
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| 417 |
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{
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| 418 |
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| 419 |
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"repo_name": "ComfyUI",
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| 420 |
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"repo_description": "The most powerful and modular diffusion model GUI, api and backend with a graph/nodes interface.",
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| 421 |
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"homepage_link": "https://www.comfy.org/",
|
| 422 |
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"closest_github_tag": "stable-diffusion"
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| 423 |
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| 424 |
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{
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| 425 |
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| 426 |
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"repo_name": "streamv2v",
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| 427 |
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"repo_description": "Official Pytorch implementation of StreamV2V. ",
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| 428 |
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"homepage_link": "https://jeff-liangf.github.io/projects/streamv2v/"
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| 429 |
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| 430 |
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| 431 |
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| 432 |
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| 433 |
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| 434 |
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| 435 |
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| 436 |
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| 437 |
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| 438 |
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| 439 |
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| 440 |
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| 441 |
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| 442 |
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| 443 |
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| 444 |
{
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| 445 |
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| 446 |
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|
| 462 |
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|
| 463 |
"homepage_link": "https://modelcontextprotocol.io"
|
| 464 |
},
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| 465 |
{
|
| 466 |
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| 467 |
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| 497 |
"homepage_link": "https://dstack.ai",
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| 498 |
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|
| 499 |
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| 500 |
{
|
| 501 |
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| 502 |
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| 504 |
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| 505 |
"category": "machine learning framework"
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| 506 |
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| 507 |
{
|
| 508 |
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|
| 509 |
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|
| 519 |
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|
| 520 |
"repo_description": "Accelerate PyTorch models with ONNX Runtime"
|
| 521 |
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|
| 522 |
{
|
| 523 |
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|
| 524 |
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|
|
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|
| 526 |
"homepage_link": "http://docs.sglang.ai/ome/",
|
| 527 |
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|
| 528 |
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|
| 529 |
{
|
| 530 |
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| 531 |
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| 537 |
"repo_description": "PyTorch Single Controller",
|
| 538 |
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|
| 539 |
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|
| 540 |
{
|
| 541 |
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|
| 542 |
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| 549 |
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|
| 550 |
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|
| 551 |
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|
| 552 |
+
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|
| 553 |
},
|
| 554 |
{
|
| 555 |
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|
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| 565 |
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|
| 566 |
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|
| 567 |
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| 568 |
{
|
| 569 |
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| 570 |
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|
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|
| 572 |
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| 573 |
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|
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| 575 |
{
|
| 576 |
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|
| 577 |
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|
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| 583 |
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|
| 584 |
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|
| 585 |
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|
| 586 |
{
|
| 587 |
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|
| 588 |
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|
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|
| 603 |
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|
| 604 |
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|
| 605 |
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| 606 |
{
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| 607 |
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| 608 |
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| 622 |
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|
| 623 |
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|
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| 625 |
{
|
| 626 |
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| 627 |
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| 636 |
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| 637 |
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| 638 |
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| 639 |
{
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| 640 |
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| 641 |
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| 679 |
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| 682 |
{
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| 683 |
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| 684 |
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| 686 |
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| 687 |
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| 689 |
{
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| 690 |
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| 691 |
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| 710 |
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| 711 |
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| 712 |
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| 713 |
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| 714 |
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| 715 |
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| 717 |
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| 724 |
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| 725 |
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| 728 |
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| 729 |
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| 730 |
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| 731 |
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| 733 |
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| 734 |
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| 736 |
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| 741 |
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| 742 |
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| 743 |
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| 745 |
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| 747 |
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|
| 748 |
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| 750 |
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| 751 |
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| 753 |
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| 754 |
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| 755 |
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| 758 |
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| 759 |
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| 761 |
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| 762 |
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| 763 |
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| 764 |
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| 765 |
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| 768 |
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|
| 769 |
+
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| 770 |
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|
| 771 |
+
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|
| 772 |
+
},
|
| 773 |
{
|
| 774 |
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|
| 775 |
"repo_name": "rocSOLVER",
|
|
|
|
| 822 |
"repo_name": "MIOpen",
|
| 823 |
"repo_description": "[DEPRECATED] Moved to ROCm/rocm-libraries repo",
|
| 824 |
"homepage_link": "https://github.com/ROCm/rocm-libraries"
|
|
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|
|
|
|
| 825 |
}
|
| 826 |
]
|