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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?

Airoboros

by Jon Durbin

Experimental model tuned primarily from synthetic data generated by the airoboros implementation of LLM self-instruction.
Text
Full
https://huggingface.co/jondurbin/airoboros-dpo-110b-3.3
Qwen1.5-110B
Airoboros-DPO-110B-3.3
Purposely left ambiguous
Individual. Primary contributor to chutes.ai.
https://github.com/jondurbin
May 2024
Availability
Training Code
Repo exists only for general fine-tuning implementation. Earlier airoboros model versions included some architecture and training information. Latest versions (>3.1.2) do not.
https://github.com/jondurbin/qlora
Base Model Data
Base model data sources nowhere documented or specified.
End User Model Data
Most data generated by airoboros, an implementation of the Self-Instruct paper. Many other data sources linked. One data source links to a 404 page. Additional data sources linked in tags but not outlined in model card.
https://huggingface.co/datasets/jondurbin/airoboros-3.2https://huggingface.co/datasets/bluemoon-fandom-1-1-rp-cleanedhttps://huggingface.co/datasets/boolqhttps://huggingface.co/datasets/jondurbin/gutenberg-dpo-v0.1https://huggingface.co/datasets/LDJnr/Capybarahttps://huggingface.co/datasets/jondurbin/cinematika-v0.1https://huggingface.co/datasets/glaiveai/glaive-function-calling-v2https://huggingface.co/datasets/grimulkan/LimaRP-augmentedhttps://huggingface.co/datasets/piqahttps://huggingface.co/datasets/Vezora/Tested-22k-Python-Alpacahttps://huggingface.co/datasets/mattpscott/airoboros-summarizationhttps://huggingface.co/datasets/unalignment/toxic-dpo-v0.2
Base Model Weights
Weights available through HuggingFace.
https://huggingface.co/Qwen/Qwen1.5-110B
End User Model Weights
Weights available through HuggingFace.
https://huggingface.co/jondurbin/airoboros-dpo-110b-3.3
Documentation
Code Documentation
Code is not very systematically documented.
https://github.com/jondurbin/qlora
Hardware Architecture
Earlier airoboros model versions included some architecture and training information. Latest versions (>3.1.2) do not.
Preprint
No preprint found.
Paper
No peer-reviewed paper found.
Modelcard
Model card contains some information, mainly relating to inference and licensing.
https://huggingface.co/jondurbin/airoboros-dpo-110b-3.3
Datasheet
Datasheets contain differing levels of documentation. Exact data used as well as data collection and curation procedure unknown. No data sheet for base model data exists.
https://huggingface.co/datasets/jondurbin/airoboros-3.2https://huggingface.co/datasets/bluemoon-fandom-1-1-rp-cleanedhttps://huggingface.co/datasets/boolqhttps://huggingface.co/datasets/jondurbin/gutenberg-dpo-v0.1https://huggingface.co/datasets/LDJnr/Capybarahttps://huggingface.co/datasets/jondurbin/cinematika-v0.1https://huggingface.co/datasets/glaiveai/glaive-function-calling-v2https://huggingface.co/datasets/grimulkan/LimaRP-augmentedhttps://huggingface.co/datasets/piqahttps://huggingface.co/datasets/Vezora/Tested-22k-Python-Alpacahttps://huggingface.co/datasets/mattpscott/airoboros-summarizationhttps://huggingface.co/datasets/unalignment/toxic-dpo-v0.2
Access
Package
Pip package available, however only supports older versions of airoboros.
https://pypi.org/project/airoboros/
API and Meta Prompts
No API found.
Licenses
Licensing left ambiguous because of murky status of OpenAI-derived Self-Instruct data.
https://huggingface.co/jondurbin/airoboros-dpo-110b-3.3#licence-and-usage-restrictions
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