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?

BitNet

by Microsoft

Native 1-bit LLM.
Text
Full
https://huggingface.co/microsoft/bitnet-b1.58-2B-4T
BitNet b1.58 2B4T
BitNet b1.58 2B4T
MIT License
Major technology company.
https://huggingface.co/microsoft
April 2025
Availability
Base Model Data
Pretraining data said to include DCLM and FineWeb-EDU. No full description provided.
https://arxiv.org/pdf/2504.12285
End User Model Data
Fine-tuning data said to include WildChat, LMSYS-Chat-1M, WizardLM-Evol-Instruct, and SlimOrca. No full description provided.
https://arxiv.org/pdf/2504.12285
Base Model Weights
Weights for base model not made available.
End User Model Weights
Weights made available on HuggingFace.
https://huggingface.co/microsoft/bitnet-b1.58-2B-4T
Training Code
Only inference code found.
https://github.com/microsoft/BitNet
Documentation
Code Documentation
No code, so no documentation
Hardware Architecture
Only inference hardware information found.
https://arxiv.org/pdf/2504.12285
Preprint
Preprint made available on arXiv.
https://arxiv.org/pdf/2504.12285
Paper
No peer-reviewed paper found.
Modelcard
Model card provides thorough information regarding architecture, fine-tuning, and evaluation. Information regarding training is provided to a lesser degree.
https://huggingface.co/microsoft/bitnet-b1.58-2B-4T
Datasheet
No datasheet found.
Access
Package
No package found.
API and Meta Prompts
Demo available. No API found.
https://bitnet-demo.azurewebsites.net/
Licenses
MIT License, an OSI-approved license.
https://huggingface.co/microsoft/bitnet-b1.58-2B-4T/blob/main/LICENSE
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 11 Jun 2025, website content last updated 10 Jun 2025.