Commit ·
81e6fe4
1
Parent(s): 3b9ace0
dstack and tflite-micro
Browse files
PyTorchConference2025_GithubRepos.json
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@@ -771,6 +771,7 @@
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{
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"repo_name": "dstack",
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"repo_link": "https://github.com/dstackai/dstack",
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"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.",
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"homepage_link": "https://dstack.ai",
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"github_topic_closest_fit": "orchestration",
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@@ -862,6 +863,7 @@
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{
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"repo_name": "tflite-micro",
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"repo_link": "https://github.com/tensorflow/tflite-micro",
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"github_about_section": "Infrastructure to enable deployment of ML models to low-power resource-constrained embedded targets (including microcontrollers and digital signal processors).",
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"contributors_all": 111,
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"contributors_2025": 19,
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{
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"repo_name": "dstack",
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"repo_link": "https://github.com/dstackai/dstack",
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"category": "container orchestration",
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"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.",
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"homepage_link": "https://dstack.ai",
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"github_topic_closest_fit": "orchestration",
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{
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"repo_name": "tflite-micro",
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"repo_link": "https://github.com/tensorflow/tflite-micro",
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"category": "ML for Microcontrollers",
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"github_about_section": "Infrastructure to enable deployment of ML models to low-power resource-constrained embedded targets (including microcontrollers and digital signal processors).",
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"contributors_all": 111,
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"contributors_2025": 19,
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