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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?

Nanbeige

by Nanbeige LLM lab

Comes in 8B and 16B versions
Text
Limited
https://huggingface.co/Nanbeige/Nanbeige2-8B-Chat
Unknown
Unknown
Apache 2.0 and bespoke community license
LLM lab.
https://huggingface.co/Nanbeige
March 2024
Availability
Training Code
github repo contains sparse but clear code for training, tuning, and inference
https://github.com/Nanbeige/Nanbeige
Base Model Data
No information on pre-training datasets except a claim of 4.5T tokens. Request for information on HF community was closed without comment.
End User Model Data
No information on finetuning and DPO datasets. Some information provided on request (see link), but official documentation not updated.
https://huggingface.co/Nanbeige/Nanbeige2-8B-Chat/discussions/2#6621e15a4d17641cf788cbd5
Base Model Weights
Base model not shared
End User Model Weights
Model weights for finetuned model shared
https://huggingface.co/Nanbeige/Nanbeige2-8B-Chat/tree/main
Documentation
Code Documentation
No documentation of the codebase
Hardware Architecture
Architecture not clearly specified
Preprint
No preprint found. Paper linked on HuggingFace was authored by LMSYS.
Paper
No paper found
Modelcard
No model card found
Datasheet
No datasheet found
Access
Package
No package found
API and Meta Prompts
No API, but HuggingFace space available
https://huggingface.co/spaces/Nanbeige/Nanbeige-Plus-Chat-v0.1
Licenses
Apache 2.0 but commercial use requires signup and an additional community license
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