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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?

SantaCoder

by BigCode

Early coder model.
Code
Full
https://huggingface.co/bigcode/santacoder
SantaCoder
SantaCoder
BigCode OpenRAIL-M v1 license agreement
Open scientific collaboration for creating LLMs.
https://huggingface.co/bigcode
December 2022
Availability
Training Code
Training done using an open-source project.
https://github.com/bigcode-project/Megatron-LM
Base Model Data
Model trained from filtered data from The Stack v1.1.
https://arxiv.org/pdf/2301.03988https://huggingface.co/datasets/bigcode/the-stack
End User Model Data
Model trained from filtered data from The Stack v1.1.
https://arxiv.org/pdf/2301.03988https://huggingface.co/datasets/bigcode/the-stack
Base Model Weights
Weights made available on HuggingFace.
https://huggingface.co/bigcode/santacoder
End User Model Weights
Weights made available on HuggingFace.
https://huggingface.co/bigcode/santacoder
Documentation
Code Documentation
Project is well-documented.
https://github.com/bigcode-project/Megatron-LM
Hardware Architecture
Training setup described in detail.
https://huggingface.co/bigcode/santacoder#training
Preprint
Preprint made available on arXiv.
https://arxiv.org/pdf/2301.03988
Paper
No paper found.
Modelcard
Model card contains the requisite information.
https://huggingface.co/bigcode/santacoder
Datasheet
Detailed data sheet available.
https://huggingface.co/datasets/bigcode/the-stack
Access
Package
No package found.
API and Meta Prompts
HuggingFace inference API available.
https://huggingface.co/bigcode/santacoder
Licenses
BigCode OpenRAIL-M v1 license agreement, not an OSI-approved license.
https://huggingface.co/bigcode/santacoder#license
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