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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?

Fietje

by Bram Vanroy

Derivative of Phi2 fine-tuned for Dutch text generation.
Text
Full
https://huggingface.co/BramVanroy/fietje-2-chat
Phi-2
Fietje-2-Chat
MIT License
Independent model creator.
https://bramvanroy.github.io/
April 2024
Availability
Base Model Data
Based on phi2 by Microsoft, for which pretraining data has not been disclosed. Phi2 documentation says only '250B tokens, combination of NLP synthetic data created by AOAI GPT-3.5 and filtered web data from Falcon RefinedWeb and SlimPajama, which was assessed by AOAI GPT-4.'.
End User Model Data
Finetuning of Phi not fully documented; derivative uses a Wikipedia and CulturaX mix for Dutch.
https://huggingface.co/datasets/BramVanroy/wikipedia_culturax_dutch
Base Model Weights
Phi 2 model weights available through HuggingFace.
https://huggingface.co/microsoft/phi-2
End User Model Weights
https://huggingface.co/BramVanroy/fietje-2-chat
Training Code
Source code for base model not available, but training for derivative well-documented in github repository.
https://github.com/BramVanroy/fietje-2
Documentation
Code Documentation
Source code for base model not available, but training for derivative model documented in exemplary detail.
https://github.com/BramVanroy/fietje-2/tree/main/training
Hardware Architecture
https://huggingface.co/BramVanroy/fietje-2-chat
Preprint
https://arxiv.org/abs/2412.15450
Paper
Modelcard
https://huggingface.co/BramVanroy/fietje-2-chat
Datasheet
No data sheet available for base model
Access
Package
API and Meta Prompts
Licenses
Model weights provided under MIT, but training data inherits unclarity and limitations from upstream models (Falcon RefinedWeb, SlimPajama).
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