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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?

GLM

by Zhipu AI

English-Chinese reasoning model.
Text
Full
https://huggingface.co/THUDM/GLM-Z1-32B-0414
GLM-4-32B-0414
GLM-Z1-32B-0414
MIT License
Zhipu AI, one of China's AI tigers.
https://github.com/THUDM
June 2024
Availability
Base Model Data
Training data not centrally made available, but described in 2022 ACL paper, appears to be mostly public datasets. Preprint also mentions "Our pre-training corpus consists of multilingual (mostly English and Chinese) documents from a mixture of different sources, including webpages, Wikipedia, books, code, and research papers", but does not go into more detail.
http://doi.org/10.18653/v1/2022.acl-long.26https://arxiv.org/abs/2406.12793
End User Model Data
Docs mention "supervised fine-tuning, feedback bootstrap, and reinforcement learning wit human feedback", but none of the datasets used are clearly specified.
Base Model Weights
Model weights made available through HuggingFace.
https://huggingface.co/THUDM/GLM-4-32B-0414
End User Model Weights
Model weights made available through HuggingFace.
https://huggingface.co/THUDM/GLM-Z1-32B-0414
Training Code
Some code made available on Github.
https://github.com/THUDM/GLM-4
Documentation
Code Documentation
No training code found.
https://github.com/THUDM/GLM-4/blob/main/README_en.md
Hardware Architecture
No hardware architecture information found.
Preprint
Describes training data, architecture, and shows performance evaluation results of various ChatGLM models.
https://arxiv.org/abs/2406.12793
Paper
ACL 2022 paper describes the training of the GLM base model, but the RLHF portion is more recent (there is also a related ICLR paper for a newer generation https://openreview.net/forum?id=-Aw0rrrPUF)
https://aclanthology.org/2022.acl-long.26/
Modelcard
Model card is provided, however only contains general and inference information.
https://huggingface.co/THUDM/GLM-Z1-32B-0414
Datasheet
No datasheet found.
Access
Package
Model available on Ollama.
https://ollama.com/library/glm4
API and Meta Prompts
Model has a paid API
https://bigmodel.cn/
Licenses
MIT License, an OSI-approved license.
https://huggingface.co/THUDM/GLM-Z1-32B-0414
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