{"id":24493027,"url":"https://github.com/fastmachinelearning/fastml-science","last_synced_at":"2025-04-14T01:40:35.117Z","repository":{"id":44932710,"uuid":"445208377","full_name":"fastmachinelearning/fastml-science","owner":"fastmachinelearning","description":"Implementations of the fastml-science bechmark models, including a standard Keras (float) and  QKeras (quantized) implementations.","archived":false,"fork":false,"pushed_at":"2023-01-16T03:20:51.000Z","size":12446,"stargazers_count":5,"open_issues_count":0,"forks_count":2,"subscribers_count":2,"default_branch":"main","last_synced_at":"2025-03-27T15:52:13.923Z","etag":null,"topics":["edge","machine-learning","real-time","science"],"latest_commit_sha":null,"homepage":"","language":"Python","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":"apache-2.0","status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/fastmachinelearning.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":null,"license":"LICENSE","code_of_conduct":null,"threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null}},"created_at":"2022-01-06T14:58:46.000Z","updated_at":"2024-03-03T17:30:22.000Z","dependencies_parsed_at":"2023-02-10T01:00:41.502Z","dependency_job_id":null,"html_url":"https://github.com/fastmachinelearning/fastml-science","commit_stats":null,"previous_names":[],"tags_count":2,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/fastmachinelearning%2Ffastml-science","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/fastmachinelearning%2Ffastml-science/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/fastmachinelearning%2Ffastml-science/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/fastmachinelearning%2Ffastml-science/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/fastmachinelearning","download_url":"https://codeload.github.com/fastmachinelearning/fastml-science/tar.gz/refs/heads/main","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":248809039,"owners_count":21164893,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2022-07-04T15:15:14.044Z","host_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub","repositories_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories","repository_names_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repository_names","owners_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners"}},"keywords":["edge","machine-learning","real-time","science"],"created_at":"2025-01-21T19:18:55.270Z","updated_at":"2025-04-14T01:40:35.089Z","avatar_url":"https://github.com/fastmachinelearning.png","language":"Python","funding_links":[],"categories":[],"sub_categories":[],"readme":"# Fast Machine Learning Science Benchmarks\n[![DOI](https://zenodo.org/badge/445208377.svg)](https://zenodo.org/badge/latestdoi/445208377)\n[![Code style: black](https://img.shields.io/badge/code%20style-black-000000.svg)](https://github.com/psf/black)\n\nImplementations of the `fastml-science` benchmark models, including a standard Keras (float) and QKeras (quantized) implementations.\n\n# jet-classify\n\n## Requirements:\nPython 3.8\n\n```\nconda env create -f environment.yml\n```\n\n## Training:\n\n```\npython3 train.py -c \u003cconfig.yml\u003e\n```\n\nUpon training completion, graphs for the ROC for each tagger, are saved to the output directory, along with a .h5 saved model file. \n\nThe benchmark includes a float/unquantized 3 layer model as well as a uniformally quantized 6b model\n\n## Sample Runs\n\n### Training Float Baseline:\n\n```\npython3 train.py -c float_baseline.yml\n```\n![Alt text](jet-classify/model/float_baseline/keras_roc_curve.png?raw=true \"Float Baseline ROC Curve\")\n\n`Model test accuracy = 0.766`\n\n`Model test weighted average AUC = 0.943`\n\n### Training Quantized Baseline:\n\n```\npython3 train.py -c quantized_baseline.yml\n```\n![Alt text](jet-classify/model/quantized_baseline/keras_roc_curve.png?raw=true \"Quantized Baseline ROC Curve\")\n\n`Model test accuracy = 0.764`\n\n`Model test weighted average AUC = 0.941`\n\n# beam-control\nWIP\n\n# sensor-data-compression\nWIP\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Ffastmachinelearning%2Ffastml-science","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Ffastmachinelearning%2Ffastml-science","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Ffastmachinelearning%2Ffastml-science/lists"}