https://github.com/amazon-science/fmcore
Running GenAI models at every scale, on every modality
Science Score: 26.0%
This score indicates how likely this project is to be science-related based on various indicators:
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○CITATION.cff file
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✓codemeta.json file
Found codemeta.json file -
✓.zenodo.json file
Found .zenodo.json file -
○DOI references
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○Academic publication links
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○Academic email domains
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○Institutional organization owner
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○JOSS paper metadata
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○Scientific vocabulary similarity
Low similarity (10.6%) to scientific vocabulary
Keywords
Repository
Running GenAI models at every scale, on every modality
Basic Info
Statistics
- Stars: 6
- Watchers: 2
- Forks: 1
- Open Issues: 8
- Releases: 7
Topics
Metadata Files
README.md
fmcore is a specialized toolkit that empowers AI scientists to break new ground by simplifying large-scale experimentation with massive Foundation Models and datasets.
A primary bottleneck in Foundation Model research is implementation overhead. With fmcore, scientists can rapidly prototype new innovations in hours instead of weeks, accelerating the path to new research breakthroughs or user experiences.
Key features: - Easy scaling of model training and inference (see examples). - Standardized interfaces for parameter tuning and evaluation. - Built-in support for distributed computing and Foundation Model parallelism.
Installation
The minimal fmcore package can be installed from PyPI:
pip install fmcore
To get all features, we recommend installing in a new Conda environment:
commandline
conda create -n fmcore python=3.11 --yes
conda activate fmcore
pip install uv
uv pip install "fmcore[all]"
License
This project is licensed under the Apache-2.0 License.
Contributing to fmcore
See CONTRIBUTING for more information.
Owner
- Name: Amazon Science
- Login: amazon-science
- Kind: organization
- Website: https://amazon.science
- Twitter: AmazonScience
- Repositories: 80
- Profile: https://github.com/amazon-science
GitHub Events
Total
- Fork event: 1
- Create event: 195
- Issues event: 9
- Release event: 10
- Watch event: 7
- Delete event: 114
- Member event: 1
- Issue comment event: 41
- Push event: 312
- Public event: 1
- Pull request review comment event: 34
- Pull request review event: 43
- Pull request event: 112
Last Year
- Fork event: 1
- Create event: 195
- Issues event: 9
- Release event: 10
- Watch event: 7
- Delete event: 114
- Member event: 1
- Issue comment event: 41
- Push event: 312
- Public event: 1
- Pull request review comment event: 34
- Pull request review event: 43
- Pull request event: 112
Issues and Pull Requests
Last synced: 6 months ago
All Time
- Total issues: 5
- Total pull requests: 53
- Average time to close issues: 29 days
- Average time to close pull requests: 4 days
- Total issue authors: 2
- Total pull request authors: 5
- Average comments per issue: 0.4
- Average comments per pull request: 0.28
- Merged pull requests: 38
- Bot issues: 0
- Bot pull requests: 12
Past Year
- Issues: 5
- Pull requests: 53
- Average time to close issues: 29 days
- Average time to close pull requests: 4 days
- Issue authors: 2
- Pull request authors: 5
- Average comments per issue: 0.4
- Average comments per pull request: 0.28
- Merged pull requests: 38
- Bot issues: 0
- Bot pull requests: 12
Top Authors
Issue Authors
- adivekar-utexas (4)
- SibaRajendran (1)
Pull Request Authors
- SibaRajendran (19)
- adivekar-utexas (15)
- dependabot[bot] (12)
- thehellmaker (5)
- sarisha19 (1)