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Parameter descriptions:

Base Model Data
Are datasources for training the base model comprehensively documented and 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 end user interacts with comprehensively documented and 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 end user interacts with made freely available?
Training Code
Is the source code of dataset processing, model training and tuning comprehensively 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 available in standardized format that provides comprehensive insight on model architecture, training, fine-tuning, and evaluation?
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?

WaveCoder

by Microsoft

Not absolutely clear that base rather than instruct-tuned model was used, but can be assumed.
Code
Full
https://huggingface.co/microsoft/wavecoder-ultra-6.7b
Deepseek-Coder-6.7B-Base
WaveCoder-Ultra-6.7B
MIT License
Major technology company.
https://huggingface.co/microsoft
July 2024
Availability
Base Model Data
Data sources of base model described only at the highest level.
https://arxiv.org/pdf/2401.14196
End User Model Data
End model makes heavy use of synthetic data which does not seem to have been published. Some non-synthetic data was used which is not described in detail.
https://arxiv.org/pdf/2312.14187
Base Model Weights
Weights made available on HuggingFace.
https://huggingface.co/deepseek-ai/deepseek-coder-6.7b-base
End User Model Weights
Weights made available on HuggingFace.
https://huggingface.co/microsoft/wavecoder-ultra-6.7b
Training Code
Training script and data processing architecture made available on GitHub. Fine-tuning script not made available.
https://github.com/microsoft/WaveCoder
Documentation
Code Documentation
Codebase is well-documented.
https://github.com/microsoft/WaveCoder
Hardware Architecture
Hardware architecture described in paper.
https://arxiv.org/pdf/2312.14187
Preprint
Preprint made available on arXiv.
https://arxiv.org/pdf/2312.14187
Paper
Paper published in ACL.
https://aclanthology.org/2024.acl-long.280/
Modelcard
Model card primarily contains information regarding inference and licensing.
https://huggingface.co/microsoft/wavecoder-ultra-6.7b
Datasheet
No datasheet found.
Access
Package
No package found.
API and Meta Prompts
No API found.
Licenses
Code licensed under MIT license, and OSI-approved license. (Base?) model licensed under DeepSeek's license.
https://huggingface.co/microsoft/wavecoder-ultra-6.7b#%F0%9F%93%96-license
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