marin-community/marin
Open-source framework for the research and development of foundation models.
Build with Backblaze B2
SDKs, agent skills, IDE extensions, and reference pipelines from Backblaze Labs. All open source.
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Where it stands
Rank, growth pace and release cadence relative to everything GStars tracks.
3 releases in the last 90 days, the latest 2 days ago, with 114 contributors on GitHub.
Peaked at #41 in the weekly ranking the week of Sep 13, its best in the past year.
Use Cases & Benefits
- Provides an open-source framework for research and development of foundation models, focusing on training large language models from data curation to evaluation.
- Enables transparent, reproducible AI model development by openly documenting all processes, experiments, and decisions including failed attempts.
- Use for training and scaling large mixture-of-experts language models for scientific and research applications.
- Use for experimenting with multi-domain foundation models including audio-text, DNA, and protein sequence modeling.
- Use for developing and benchmarking custom language models on diverse datasets with scalable compute resources like TPU and GPU clusters.
Should you depend on it?
License terms, project hygiene and risks, from GitHub metadata and GStars' snapshots.
License
Apache 2.0
Permissive: commercial use, modification and redistribution are allowed with attribution; includes an explicit patent grant from contributors.
Community files
- README: present
- Contributing guide: present
- Code of conduct: present
Watch-outs
No watch-outs from GStars' checks.
General guidance from repository metadata, not legal advice. How we score
From the README
"I am not afraid of storms, for I am learning how to sail my ship."
– Louisa May Alcott
Marin is a research program, software platform, and community for the research and development of foundation models.
Marin's concern is training large language models. This includes data curation, transformation, filtering, tokenization, pretraining, posttraining, and evaluation. Beyond the artifacts, software, and infrastructure, behind these models, Marin is committed to openly sharing all of the process knowledge required to build these models.
Marin's core value is open development. We document our processes, experiments, and decisions as they happen. Every step, from raw data to the final model, is recorded. Failed experiments are part of that record.
Marin has also been used for building audio-text models, DNA, and protein models. We encourage this work through the use of Marin as a library, in marin/experiments.
Our current focus is pretraining, from scratch, and posttraining a large (5e24 model-FLOPs, 500 billion+ total parameters) mixture-of-experts model to succeed on tasks of importance to scientists and researchers.
Daily snapshots
Stars gained per day, and how forks and open issues moved, from GStars' daily snapshots
+1,663 stars over 72 days across 23 snapshot days; best day +266 on Aug 27.
Forks
342+131
Open issues
761+187
Compared with peers in Backend
Fastest-growing repositories GStars tracks in this cohort for the week of Nov 1, by 7-day star growth
| Repository | Stars | +7d | Health | Last release |
|---|---|---|---|---|
| anthropics/skills | 187.8K | +2.9K | 15 | — |
| DuarteSantos8/openGym | 19.7K | +2.4K | 60 | 2 days ago |
| shiyu-coder/Kronos | 47.0K | +2.3K | 16 | — |
| NationalSecurityAgency/ghidra | 98.2K | +2.3K | 64 | 14 days ago |
| microsoft/VibeVoice | 56.0K | +1.1K | 29 | — |
| marin-community/marin | 4.1K | — | 65 | 2 days ago |
| Category median | 56.0K | +2.3K | 29 | — |
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