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Parameter descriptions:

Base Model Data
Are datasources for training the base model comprehensively documented and freely made available? In case a distinction between base (foundation) and end (user) model is not applicable, this mirrors the end model data entries.
End User Model Data
Are datasources for training the model that the enduser interacts with comprehensively documented and freely made available?
Base Model Weights
Are the weights of the base models made freely available? In case a distinction between base (foundation) and end (user) model is not applicable, this mirrors the end model data entries.
End User Model Weights
Are the weights of the model that the enduser interacts with made freely available?
Training Code
Is the source code of datasource processing, model training and tuining comprehensively and freely made available?
Code Documentation
Is the source code of datasource processing, model training and tuning comprehensively documented?
Hardware Architecture
Is the hardware architecture used for datasource processing and model training comprehensively documented?
Preprint
Are archived preprint(s) are available that detail all major parts of the system including datasource processing, model training and tuning steps?
Paper
Are peer-reviewed scientific publications available that detail all major parts of the system including datasource processing, model training and tuning steps?
Modelcard
Is a model card in standardized format available that provides comprehensive insight on model architecture, training, fine-tuning, and evaluation are available?
Datasheet
Is a datasheet as defined in "Datasheets for Datasets" (Gebru et al. 2021) available?
Package
Is a packaged release of the model available on a software repository (e.g. a Python Package Index, Homebrew)?
API and Meta Prompts
Is an API available that provides unrestricted access to the model (other than security and CDN restrictions)? If applicable, this entry also collects information on the use and availability of meta prompts.
Licenses
Is the project fully covered by Open Source Initiative (OSI)-approved licenses, including all data sources and training pipeline code?

Koala

by BAIR

From the documentation 'Koala is fine-tuned on freely available interaction data scraped from the web, but with a specific focus on data that includes interaction with highly capable closed-source models such as ChatGPT.'
Text
Full
https://bair.berkeley.edu/blog/2023/04/03/koala/
(undefined)
(undefined)
Mixed
Berkeley Artificial Intelligence Research
https://bair.berkeley.edu/
March 2023
Availability
Training Code
Code scattered across projects and repositories
https://github.com/young-geng/EasyLM
Base Model Data
Repo contains data pipeline for preprocessing. Based on LLaMA which is said to be based on 'publicly available datasets' which are not made directly available.
https://github.com/young-geng/koala_data_pipeline
End User Model Data
Datasets described in blog post but not all made available
https://bair.berkeley.edu/blog/2023/04/03/koala/#datasets-and-training
Base Model Weights
Model weights ostensibly made available as a diff against LLaMA, however the folder containing the weights is empty.
https://drive.google.com/drive/folders/10f7wrlAFoPIy-TECHsx9DKIvbQYunCfl
End User Model Weights
RL weights not made available separately
Documentation
Code Documentation
Code scattered across various repositories and not systematically documented.
https://github.com/young-geng/EasyLM
Hardware Architecture
Architecture visually illustrated and described in some detail.
https://github.com/young-geng/EasyLM
Preprint
No preprint available
Paper
No peer-reviewed paper
Modelcard
No model card available
Datasheet
No systematic data sheet available
Access
Package
No package available
API and Meta Prompts
No API available
Licenses
Licensing is 'subject to the model License of LLaMA, Terms of Use of the data generated by OpenAI, and Privacy Practices of ShareGPT'
https://huggingface.co/young-geng/koala#license
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