The IndexGuidesNews
AboutContribute

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?

SQLCoder

by Defog.ai

Text-to-SQL model.
Code
Latest
https://huggingface.co/defog/sqlcoder-7b-2
CodeLlama-7B
SQLCoder-7B-2
CC-BY-SA-4.0
Organization creating code generation for LLMs.
https://huggingface.co/defog
February 2024
Availability
Base Model Data
Proprietary dataset used.
End User Model Data
Data sources published in GitHub repo
https://github.com/defog-ai/sql-eval
Base Model Weights
Gated model available on HuggingFace.
https://huggingface.co/meta-llama/CodeLlama-7b-Instruct-hf
End User Model Weights
Weights made available on HuggingFace.
https://huggingface.co/defog/sqlcoder-7b-2
Training Code
GitHub exists, but mainly contains inference code. Training procedure broadly outlined in text.
https://github.com/defog-ai/sqlcoderhttps://defog.ai/blog/open-sourcing-sqlcoder2-7bhttps://defog.ai/blog/sqlcoder2-technical-details
Documentation
Code Documentation
No code, so no documentation.
Hardware Architecture
No description of hardware architecture found.
Preprint
Info about model released through blog post.
https://defog.ai/blog/open-sourcing-sqlcoder2-7b
Paper
No peer-reviewed paper found.
Modelcard
Model card provides a decent amount of information.
https://huggingface.co/defog/sqlcoder-7b-2
Datasheet
No datasheet found.
Access
Package
Package available through PyPi.
https://pypi.org/project/sqlcoder/
API and Meta Prompts
Demo available
https://defog.ai/sqlcoder-demo
Licenses
CC-BY-SA-4.0.
https://huggingface.co/defog/sqlcoder-7b-2
Is this information not up to date?
Contribute here ->

Supported by the Centre for Language Studies and the Dutch Research Council. Website design & development © 2024 by BSTN. This version of the index generated 12 Sep 2025, website content last updated 04 Sep 2025.