{"id":18871771,"url":"https://github.com/chiphuyen/metaflow-transformers-tutorials","last_synced_at":"2025-07-05T07:32:52.315Z","repository":{"id":66475691,"uuid":"426880624","full_name":"chiphuyen/metaflow-transformers-tutorials","owner":"chiphuyen","description":"Metaflow tutorials for ODSC West 2021","archived":false,"fork":false,"pushed_at":"2021-11-16T19:08:26.000Z","size":26015,"stargazers_count":64,"open_issues_count":0,"forks_count":6,"subscribers_count":4,"default_branch":"main","last_synced_at":"2025-03-28T04:41:39.522Z","etag":null,"topics":["machine-learning","metaflow"],"latest_commit_sha":null,"homepage":"","language":"Jupyter Notebook","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":null,"status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/chiphuyen.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":null,"license":null,"code_of_conduct":null,"threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null,"governance":null,"roadmap":null,"authors":null,"dei":null,"publiccode":null,"codemeta":null}},"created_at":"2021-11-11T05:21:54.000Z","updated_at":"2025-01-12T18:58:30.000Z","dependencies_parsed_at":null,"dependency_job_id":"ceb6e587-a7c2-49e0-876b-6953b6532465","html_url":"https://github.com/chiphuyen/metaflow-transformers-tutorials","commit_stats":null,"previous_names":[],"tags_count":0,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/chiphuyen%2Fmetaflow-transformers-tutorials","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/chiphuyen%2Fmetaflow-transformers-tutorials/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/chiphuyen%2Fmetaflow-transformers-tutorials/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/chiphuyen%2Fmetaflow-transformers-tutorials/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/chiphuyen","download_url":"https://codeload.github.com/chiphuyen/metaflow-transformers-tutorials/tar.gz/refs/heads/main","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":248906720,"owners_count":21181207,"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":["machine-learning","metaflow"],"created_at":"2024-11-08T05:27:19.002Z","updated_at":"2025-07-05T07:32:52.308Z","avatar_url":"https://github.com/chiphuyen.png","language":"Jupyter Notebook","funding_links":[],"categories":["Examples \u0026 Tutorials"],"sub_categories":[],"readme":"\nFirst, get started with Metaflow by executing these simple flows:\n\n1. `helloworld.py` - a simple hello world flow\n2. `counter_branch.py` - test artifacts\n3. `parameters.py` - test parameters\n4. `foreach.py` - test foreaches (parallel tasks)\n\nAfter these simple examples, you can take a look at a more realistic case:\n\nIn this tutorial, we'll fine-tune a sentiment analysis model on top of\nHuggingFace's DistilBERT model with the IMDB dataset.\n\nFirst, we'll show how to do it without Metaflow.\n1. sent_analysis_train.py is the training code (6-7 minutes on the small dataset of 100 samples on my Mac)\n2. sent_analysis_predict.py is the prediction code (30 seconds)\n\nWe'll do live coding to show how to convert the training code to Metaflow.\nSee sent_analysis_metaflow.py for instructions.\n\nWe'll run `python sent_analysis_metaflow.py --no-pylint run --mode small`\nto train a model on 100 samples locally.\n\nWe'll show how Metaflow automatically saves trained models which we can access for predictions.\n\nWe'll use @batch to train the full dataset (40,000 samples) on AWS.\nWe'll need GPU since it'll take a while for the full data on CPU.\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fchiphuyen%2Fmetaflow-transformers-tutorials","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fchiphuyen%2Fmetaflow-transformers-tutorials","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fchiphuyen%2Fmetaflow-transformers-tutorials/lists"}