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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?

DeepHermes

by Nous Research

Hybrid reasoning model based on Llama.
Text
Full
https://huggingface.co/NousResearch/Hermes-4-70B
Llama-3.1-70B
Hermes-4-70B
Llama 3 Community License Agreement
AI research initiative.
https://nousresearch.com/
August 2025
Availability
Base Model Data
based on LLama3
End User Model Data
Mix of synthetic data. Data for previous model version made available.
https://huggingface.co/datasets/NousResearch/Hermes-3-Dataset
Base Model Weights
Inspecting the training weights requires signing Meta Llama 3.1's bespoke 'community license', not an OSI recognised open license
https://huggingface.co/meta-llama/Meta-Llama-3.1-70B
End User Model Weights
Model made available through HuggingFace.
https://huggingface.co/NousResearch/Hermes-4-70B
Training Code
Training code published on GitHub.
https://github.com/NousResearch/atropos
Documentation
Code Documentation
Code comprehensively documented.
https://huggingface.co/datasets/NousResearch/Hermes-3-Dataset
Hardware Architecture
Hardware setup comprehensively documented in paper.
https://arxiv.org/pdf/2508.18255
Preprint
Preprint published on arXiv.
https://arxiv.org/pdf/2508.18255
Paper
No peer-reviewed paper found.
Modelcard
Model card primarily contains usage information.
https://huggingface.co/NousResearch/Hermes-4-70B
Datasheet
No datasheet found.
Access
Package
No package found.
API and Meta Prompts
No API found.
Licenses
Meta custom license
https://huggingface.co/datasets/NousResearch/Hermes-3-Dataset
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