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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?

QwQ-32B

by Alibaba Cloud

Reasoning model based on Qwen2.5-32B.
Text
Latest
https://huggingface.co/Qwen/QwQ-32B
Qwen2.5-32B
QwQ-32B
Apache-2.0
Alibaba Cloud, a subdivision of the Chinese multinational technology company Alibaba.
https://www.alibabacloud.com/
March 2025
Availability
Training Code
Repository provides sparse source code and some examples for SFT
https://github.com/QwenLM/Qwen2.5
Base Model Data
Pretraining data not specified or documented.
End User Model Data
Data not specified or documented.
Base Model Weights
Model weights made available on HuggingFace.
https://huggingface.co/Qwen/Qwen2.5-32B
End User Model Weights
Model weights made available on HuggingFace.
https://huggingface.co/Qwen/QwQ-32B
Documentation
Code Documentation
Repository is fairly well-documented.
https://github.com/QwenLM/Qwen2.5
Hardware Architecture
No description of hardware architecture found.
Preprint
Preprint exists for base model, subsequent stages described in blog posts.
https://arxiv.org/pdf/2407.10671https://qwenlm.github.io/blog/qwen2.5/https://qwenlm.github.io/blog/qwq-32b/
Paper
No peer-reviewed paper found.
Modelcard
Model card primarily contains usage instructions.
https://huggingface.co/Qwen/QwQ-32B
Datasheet
No datasheet found.
Access
Package
Model available on Ollama.
https://ollama.com/library/qwq
API and Meta Prompts
Model available through HuggingFace space.
https://huggingface.co/spaces/Qwen/QwQ-32B-Demo
Licenses
Model released under Apache-2.0, an OSI-approved license.
https://qwenlm.github.io/blog/qwq-32b/
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