The IndexGuidesNews
AboutContribute

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?

Viking

by Silo AI, TurkuNLP, High Performance Language Technologies (HPLT)

Multilingual model trained on Nordic languages, English, and code. Also available as 7B and 13B models.
Text
Full
https://huggingface.co/LumiOpen/Viking-33B
Viking-33B
Viking-33B
Apache 2.0
Silo AI was acquired by AMD in August 2024
[ "https://www.silo.ai", "https://turkunlp.org", "https://hplt-project.org" ]
May 2024
Availability
Training Code
No details of training code have been released
Base Model Data
Trained on SlimPajama, Starcoder and mc4. However, exact details are yet to be published.
End User Model Data
Same as base model. No additional fine-tuning data specified.
Base Model Weights
Model weights available at various training checkpoints.
https://huggingface.co/LumiOpen/Viking-7B
End User Model Weights
https://huggingface.co/LumiOpen/Viking-7B
Documentation
Code Documentation
Hardware Architecture
Uses a LLaMA-like GPT architecture. However, no further details have been provided.
Preprint
No preprint found
Paper
No peer reviewed paper found
Modelcard
Model card provides a broad overview; more detailed documentation is forthcoming.
https://huggingface.co/LumiOpen/Viking-33B
Datasheet
On HuggingFace "Viking is being trained on a 2 trillion token mixed dataset of English, Finnish, Swedish, Danish, Norwegian, Icelandic and code. Full details will be published soon."
Access
Package
No Packages published
API and Meta Prompts
Licenses
Apache 2.0, unclear if both weights and code are under it though.
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 09 Apr 2025, website content last updated 23 Apr 2025.