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Facts
| Fact | microsoft/evodiff Generation of protein sequences and evolutionary alignments via discrete diffusion models | sarus-tech/tf2-published-models Sarus implementation of classical ML models. The models are implemented using the Keras API of tensorflow 2. Vizualization are implemented and can be seen in tensorboard. |
|---|---|---|
| Stars | 690 | 37 |
| Net stars, last 30 days | +4 | Not recorded |
| Largest star day | +2 on Jun 23, 2026 | Not recorded |
| Milestone reached in the record | None | None |
| Forks | 115 | 7 |
| Language | Python | Python |
| License | MIT | APACHE-2.0 |
| Created | Jun 7, 2022 | Jul 6, 2020 |
| Last push | Jan 15, 2026 | Sep 23, 2021 |
| Archived | No | No |
| Health facts: Maintenance | 1 of 4 checks (2 without data) | 1 of 4 checks (2 without data) |
| Health facts: Releases | 1 of 3 checks (1 without data) | 0 of 3 checks (2 without data) |
| Health facts: Security practice | 0 of 1 check (1 without data) | 0 of 1 check (1 without data) |
| Health facts: Community files | 1 of 3 checks (2 without data) | 1 of 3 checks (2 without data) |
| Commits, last 13 weeks | No data | No data |
| Weeks with commits, last 52 | No data | No data |
| In the Repository Index since | Oct 22, 2026 | Oct 22, 2026 |
Topics that all of them have on the Repository Host: generative-model. The facts come from the Repository Host and from the Star History that AwesomeRepos records. A shared topic does not mean that one repository can replace another. Each Health Facts row is one dimension alone. AwesomeRepos does not add them into one score. How each check is defined