CT-LLM.yaml

---
# 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: Academic (Research community)

# Training compute:
# - Base model training compute: >= 1.81e+22 FLOP +- 0.5 OoM (param count & dataset size)
# - End model training compute: unknown (likely negligible)

system:
    name: CT-LLM
    link: https://huggingface.co/m-a-p/CT-LLM-SFT-DPO
    type: text
    performanceclass: full
    basemodelname: CT-LLM-Base
    endmodelname: CT-LLM-SFT-DPO
    endmodellicense: Apache-2.0
    releasedate: 2024-04
    notes: Chinese-only model

org:
    name: Multimodal Art Projection
    link: https://m-a-p.ai/
    notes: Open-source AI research community.

# availability:
datasources_basemodel:
    class: closed
    link: 
    notes: No information about data sources found. 

datasources_endmodel:
    class: partial
    link: ["https://huggingface.co/m-a-p/CT-LLM-SFT-DPO", "https://arxiv.org/pdf/2404.04167", "https://huggingface.co/datasets/m-a-p/COIG-CQIA", "https://data.baai.ac.cn/details/OL-CC", "https://huggingface.co/datasets/BAAI/COIG-PC", "https://huggingface.co/datasets/argilla/OpenHermesPreferences", "https://huggingface.co/datasets/Skepsun/cvalues_rlhf", "https://github.com/HIT-SCIR/huozi", "https://huggingface.co/datasets/liyucheng/zhihu_rlhf_3k", "https://github.com/hiyouga/LlamaFactory", "https://github.com/PKU-Alignment/beavertails"]
    notes: List of datasets provided. Synthetic data used and not disclosed.

weights_basemodel:
    class: open
    link: https://huggingface.co/m-a-p/CT-LLM-Base
    notes: 

weights_endmodel:
    class: open
    link: https://huggingface.co/m-a-p/CT-LLM-SFT-DPO
    notes: 

trainingcode:
    class: partial
    link: https://github.com/multimodal-art-projection/Megatron-LM-NEO/tree/5215161b12485e5f09eb93b3997d7f3233d9fda9/neo
    notes: 

# documentation:
code:
    class: open
    link:  https://github.com/Chinese-Tiny-LLM/Chinese-Tiny-LLM
    notes: 

hardware_architecture:
    class: partial
    link: https://github.com/Chinese-Tiny-LLM/Chinese-Tiny-LLM?tab=readme-ov-file
    notes: 

preprint:
    class: open
    link: https://arxiv.org/abs/2404.04167
    notes: 

paper:
    class: open
    link: https://openreview.net/forum?id=RCdoMrg4I0
    notes: Paper accepted at COLM.

modelcard:
    class: open
    link: https://huggingface.co/m-a-p/CT-LLM-SFT-DPO
    notes: 

datasheet:
    class: closed
    link: 
    notes: 

# access:
licenses:
    class: partial
    link: ["https://huggingface.co/m-a-p/CT-LLM-SFT-DPO", "https://arxiv.org/pdf/2404.04167", "https://huggingface.co/datasets/m-a-p/COIG-CQIA", "https://data.baai.ac.cn/details/OL-CC", "https://huggingface.co/datasets/BAAI/COIG-PC", "https://huggingface.co/datasets/argilla/OpenHermesPreferences", "https://huggingface.co/datasets/Skepsun/cvalues_rlhf", "https://github.com/HIT-SCIR/huozi", "https://huggingface.co/datasets/liyucheng/zhihu_rlhf_3k", "https://github.com/hiyouga/LlamaFactory", "https://github.com/PKU-Alignment/beavertails"]
    notes: "Weights: Apache-2.0. Code: CC-BY-4.0. Data: various licenses, some unknown and/or unclear."