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CodeUp.yaml

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---
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# Thank you for contributing!
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# In filling out this yaml file, please follow the criteria as described here:
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# https://osai-index.eu/contribute
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# You're free to build on this work and reuse the data. It is licensed under CC-BY 4.0, with the
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# stipulation that attribution should come in the form of a link to https://osai-index.eu/
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# and a citation to the peer-reviewed paper in which the dataset & criteria were published:
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# 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).
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# Organization tags:
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# - National origin: China
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# - Contributor type: Academic (University)
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system:
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name: CodeUp
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link: https://huggingface.co/juyongjiang/CodeUp-Llama-3-8B
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type: code
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performanceclass: full
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basemodelname: Meta-Llama-3-8B
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endmodelname: CodeUp-Llama-3-8B
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endmodellicense: Stable-Diffusion-OpenRail++-M License and Apache-2.0 and CC-BY-NC-4.0
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releasedate: 2024-12
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notes: Multilingual code generation model.
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org:
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name: John
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link: https://github.com/juyongjiang
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notes: PhD student at HKUST.
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# availability:
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datasources_basemodel:
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class: closed
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link:
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notes: Data nowhere disclosed or documented, and described only in the vaguest terms in a release blog post
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datasources_endmodel:
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class: open
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link: ["https://huggingface.co/datasets/WizardLMTeam/WizardLM_evol_instruct_V2_196k", "https://huggingface.co/datasets/meta-math/MetaMathQA", "https://huggingface.co/datasets/theblackcat102/evol-codealpaca-v1"]
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notes: Datasets used for tuning published on HuggingFace.
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weights_basemodel:
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class: partial
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link: https://ai.meta.com/resources/models-and-libraries/llama-downloads/
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notes: Download only after requesting access; requires signing a consent form
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weights_endmodel:
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class: partial
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link: https://huggingface.co/juyongjiang/CodeUp-Llama-3-8B
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notes: Model available on HuggingFace.
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trainingcode:
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class: partial
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link: ["https://github.com/meta-llama/llama3", "https://github.com/juyongjiang/CodeUp"]
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notes: Base model repository only offers minimal code. End model repo contains some code.
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# documentation:
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code:
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class: partial
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link: https://github.com/juyongjiang/CodeUp/blob/master/README.md
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notes: End model repo documented.
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hardware_architecture:
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class: partial
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link: https://ai.meta.com/research/publications/llama-2-open-foundation-and-fine-tuned-chat-models/
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notes: Architecture sketched in glossy blog post.
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preprint:
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class: partial
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link: https://arxiv.org/pdf/2406.00515
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notes: Preprint exists for a very tangentially related document.
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paper:
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class: closed
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link:
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notes: No peer-reviewed paper found.
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modelcard:
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class: partial
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link: https://huggingface.co/meta-llama/CodeLlama-70b-Instruct-hf
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notes: Model card provides some information about training and inference, however mostly contains usage instructions.
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datasheet:
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class: partial
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link: ["https://huggingface.co/datasets/WizardLMTeam/WizardLM_evol_instruct_V2_196k", "https://huggingface.co/datasets/meta-math/MetaMathQA", "https://huggingface.co/datasets/theblackcat102/evol-codealpaca-v1"]
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notes: Datasheets found with various levels of detail.
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# access:
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package:
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class: closed
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link:
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notes: No package found.
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api:
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class: closed
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link:
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notes: No API found.
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metaprompt: closed
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licenses:
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class: partial
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link: https://huggingface.co/juyongjiang/CodeUp-Llama-3-8B
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notes: Stable-Diffusion-OpenRail++-M License and Apache-2.0 and CC-BY-NC-4.0. Not all OSI-approved licenses.

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