main-database/Granite Code.yaml at preview · Language-Technology-Assessment/main-database · GitHub

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---
# Thank you for contributing!
# In filling out this yaml file, please follow the criteria as described here:
# https://osai-index.eu/contribute

# You're free to build on this work and reuse the data. It is licensed under CC-BY 4.0, with the
# stipulation that attribution should come in the form of a link to https://osai-index.eu/
# and a citation to the peer-reviewed paper in which the dataset & criteria were published:

# Liesenfeld, A. and Dingemanse, M., 2024. Rethinking open source generative AI: open-washing and the EU AI Act. In Proceedings of the 2024 ACM Conference on Fairness, Accountability, and Transparency (pp. 1774-1787).

# Organization tags:
# - National origin: United States
# - Contributor type: Non-academic (Company)

system:
    name: Granite Code
    link: https://huggingface.co/ibm-granite/granite-20b-code-instruct-r1.1
    type: code
    performanceclass: full
    basemodelname: Granite-20B-Code-Base-r1.1
    endmodelname: Granite-20B-Code-Instruct-r1.1
    endmodellicense: Apache-2.0
    releasedate: 2024-07
    notes: Open foundation code model.

org:
    name: IBM
    link: https://www.ibm.com/
    notes: Major technology company.

# availability:
datasources_basemodel:
    class: open
    link: ["https://huggingface.co/datasets/open-web-math/open-web-math", "https://huggingface.co/datasets/codeparrot/github-code-clean", "https://huggingface.co/datasets/bigcode/starcoderdata"]
    notes: Base model data shared on HuggingFace.

datasources_endmodel:
    class: open
    link: ["https://huggingface.co/datasets/bigcode/commitpackft", "https://huggingface.co/datasets/meta-math/MetaMathQA", "https://huggingface.co/datasets/TIGER-Lab/MathInstruct"]
    notes: End model data shared on HuggingFace.

weights_basemodel:
    class: open
    link: https://huggingface.co/ibm-granite/granite-20b-code-base-r1.1
    notes: Weights made available on HuggingFace.

weights_endmodel:
    class: open
    link: https://huggingface.co/ibm-granite/granite-20b-code-instruct-r1.1
    notes: Weights made available on HuggingFace.

trainingcode:
    class: closed
    link: https://github.com/ibm-granite/granite-code-models
    notes: Repo exists, but does not contain training code.

# documentation:
code:
    class: closed
    link: https://github.com/ibm-granite/granite-code-models
    notes: No code, so no documentation.

hardware_architecture:
    class: open
    link: https://github.com/ibm-granite/granite-code-models
    notes: Hardware architecture outlined in model card.

preprint:
    class: open
    link: https://arxiv.org/pdf/2405.04324
    notes: Preprint made available on arXiv.

paper:
    class: closed
    link:
    notes: No peer-reviewed paper found.

modelcard:
    class: partial
    link: https://huggingface.co/ibm-granite/granite-20b-code-instruct-r1.1
    notes: Model card contains information about training and evaluation.

datasheet:
    class: partial
    link: ["https://huggingface.co/datasets/open-web-math/open-web-math", "https://huggingface.co/datasets/codeparrot/github-code-clean", "https://huggingface.co/datasets/bigcode/starcoderdata", "https://huggingface.co/datasets/bigcode/commitpackft", "https://huggingface.co/datasets/meta-math/MetaMathQA", "https://huggingface.co/datasets/TIGER-Lab/MathInstruct"]
    notes: Some data sources are well-documented, but not all.

# access:
licenses:
    class: open
    link: https://huggingface.co/ibm-granite/granite-20b-code-instruct-r1.1
    notes: Apache-2.0, an OSI-approved license.