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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?

DeepSeek R1

by DeepSeek

Mixture-of-experts reasoning model.
Text
Latest
https://github.com/deepseek-ai/DeepSeek-R1
DeepSeek-V3-Base
DeepSeek-R1
DeepSeek License Agreement
DeepSeek (深度求索), founded in 2023, is a Chinese company dedicated to making AGI a reality.
https://www.deepseek.com/
January 2025
Availability
Training Code
Repository does not contain code.
https://github.com/deepseek-ai/DeepSeek-R1
Base Model Data
Pretraining data not specified or documented besides the claim that it amounts to 14.8T tokens in Chinese and English. Proprietary dataset.
End User Model Data
Post-training data not specified or documented. Said to include '1.5M instances'.
Base Model Weights
https://huggingface.co/deepseek-ai/DeepSeek-V3-Base
End User Model Weights
https://huggingface.co/deepseek-ai/DeepSeek-R1
Documentation
Code Documentation
No code, so no documentation.
https://github.com/deepseek-ai/DeepSeek-V3/
Hardware Architecture
Model architecture described in a fair bit of detail in base model technical report.
https://arxiv.org/pdf/2412.19437
Preprint
Paper provides information about techniques used for constructing model, but nothing on pre- or post-training data.
https://arxiv.org/pdf/2501.12948
Paper
No peer-reviewed paper found.
Modelcard
Model card on HF provides basic summary but no info on intended downstream uses, scope, biases, risks and limitations.
https://huggingface.co/deepseek-ai/DeepSeek-V3-Base
Datasheet
No datasheet provided.
Access
Package
Model available on Ollama.
https://ollama.com/library/deepseek-r1
API and Meta Prompts
Available through various APIs.
platform.deepseek.com
Licenses
MIT License and a separate Model License. Derived model (R1) claims to be fully licensed through MIT.
https://huggingface.co/deepseek-ai/DeepSeek-V3-Base/blob/main/LICENSE-MODEL
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