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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?

Gemma

by Google AI

Model weights and developer tools
Text
Latest
https://huggingface.co/google/gemma-3-27b-it
Gemma-3-27B-PT
Gemma-3-27B-IT
Gemma Terms of Use
Major technology company, operator of Google Search.
https://ai.google
March 2025
Availability
Training Code
No pre-training or instructing-tuning code made available. Some developer tools available.
https://github.com/google-deepmind/gemma
Base Model Data
No details provided on pre-training data.
End User Model Data
No details found for instruction-tuning data.
Base Model Weights
Gated model available through HuggingFace.
https://huggingface.co/google/gemma-3-27b-pt
End User Model Weights
Gated model available through HuggingFace.
https://huggingface.co/google/gemma-3-27b-it
Documentation
Code Documentation
No pretraining or finetuning code found. No code documentation except for deployment of the open weights.
Hardware Architecture
Architecture described in detail in technical report.
https://storage.googleapis.com/deepmind-media/gemma/Gemma3Report.pdf
Preprint
Preprint available on Google's API servers.
https://storage.googleapis.com/deepmind-media/gemma/Gemma3Report.pdf
Paper
No paper found.
Modelcard
Model card provides the requisite information.
https://huggingface.co/google/gemma-3-27b-it
Datasheet
No datasheet found.
Access
Package
Package available on PyPi.
https://pypi.org/project/gemma/
API and Meta Prompts
No API found.
Licenses
Bespoke Gemma Community License Agreement and restrictive Terms of Use, neither open in the sense of OSI. Only Inference code shared under Apache 2.0.
https://huggingface.co/google/gemma-3-27b-it#gemma-3-model-card
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