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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?

LongAlign

by Zhipu AI

Recipe for long-context LLM alignment.
Text
Limited
https://huggingface.co/THUDM/LongAlign-13B-64k
Llama-2-13B
LongAlign-13B-64k
Apache-2.0
Zhipu AI, one of China's AI tigers.
https://github.com/THUDM
January 2024
Availability
Base Model Data
Data nowhere disclosed or documented, and described only in the vaguest terms in a corporate preprint released by Meta.
https://ai.meta.com/research/publications/llama-2-open-foundation-and-fine-tuned-chat-models/
End User Model Data
some on HF
https://huggingface.co/datasets/THUDM/LongAlign-10k
Base Model Weights
Download only after requesting access; requires signing a consent form
https://ai.meta.com/resources/models-and-libraries/llama-downloads/
End User Model Weights
https://huggingface.co/THUDM/LongAlign-13B-64k
Training Code
Documentation
Code Documentation
Hardware Architecture
Preprint
https://arxiv.org/pdf/2401.18058
Paper
https://aclanthology.org/2024.findings-emnlp.74/
Modelcard
Datasheet
No datasheet found.
Access
Package
API and Meta Prompts
Licenses
weights under Apache 2
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