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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?

Ling

by Inclusion AI

Reasoning model with claims of comparable performance to DeepSeek-R1.
Text
Latest
https://huggingface.co/inclusionAI/Ling-1T
Ling-1T
Ring-1T
MIT License
Inclusion AI, an organization within the Ant Group, an affiliate company of the Chinese multinational technology company Alibaba.
https://github.com/inclusionAI
October 2025
Availability
Base Model Data
Pretraining datasets not disclosed.
End User Model Data
Finetuning datasets published on HuggingFace.
https://huggingface.co/inclusionAI/datasets
Base Model Weights
No base model made available.
End User Model Weights
Model weights made available on HuggingFace.
https://huggingface.co/inclusionAI/Ring-1T
Training Code
Training code made available on GitHub.
https://github.com/inclusionAI/Ling-V2https://github.com/inclusionAI/Ring-V2
Documentation
Code Documentation
Repository is well-documented.
https://github.com/inclusionAI/Ling-V2https://github.com/inclusionAI/Ring-V2
Hardware Architecture
Hardware architecture outlined in preprint.
https://arxiv.org/pdf/2510.22115
Preprint
Preprint published on arXiv.
https://arxiv.org/pdf/2510.22115
Paper
No peer-reviewed paper found.
Modelcard
Model card contains some useful info.
https://huggingface.co/inclusionAI/Ring-1T
Datasheet
No datasheet found.
Access
Package
No package found.
API and Meta Prompts
Inference provider through HuggingFace.
https://huggingface.co/inclusionAI/Ling-1T
Licenses
Model released under MIT license, an OSI-approved license.
https://huggingface.co/inclusionAI/Ling-1T#license
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