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Infinity-Instruct.yaml
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104 lines (85 loc) · 2.37 KB
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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: China
# - Contributor type: Non-academic (Research institution)
system:
name: Infinity-Instruct
link: https://huggingface.co/BAAI/Infinity-Instruct-7M-Gen-Llama3_1-70B
type: text
performanceclass: limited
basemodelname: Llama-3.1-70B
endmodelname: Infinity-Instruct-7M-Gen-Llama3.1-70B
endmodellicense: Llama 3.1 Community License Agreement
releasedate: 2024-08
notes: Open-source model designed to test the performance of the Infinity-Instruct dataset.
org:
name: Beijing Academy of Artificial Intelligence
link: https://www.baai.ac.cn/en/
notes: Chinese non-profit AI lab.
# availability:
datasources_basemodel:
class: closed
link:
notes: based on Llama3
datasources_endmodel:
class: partial
link: https://huggingface.co/datasets/BAAI/Infinity-Instruct
notes: partially on HF
weights_basemodel:
class: open
link:
notes:
weights_endmodel:
class: open
link: https://huggingface.co/BAAI/Infinity-Instruct-7M-Gen-Llama3_1-70B
notes:
trainingcode:
class: closed
link:
notes: soon to be released
# documentation:
code:
class: closed
link:
notes:
hardware_architecture:
class: closed
link:
notes:
preprint:
class: closed
link:
notes: dead link
paper:
class: closed
link:
notes:
modelcard:
class: open
link: https://huggingface.co/BAAI/Infinity-Instruct-7M-Gen-Llama3_1-70B
notes:
datasheet:
class: closed
link:
notes:
# access:
package:
class: closed
link:
notes:
api:
class: closed
link:
notes:
metaprompt: closed
licenses:
class: closed
link:
notes: weights under meta custom license