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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?

Amber

by LLM360

Model released to make LLM training knowledge accessible to all.
Text
Limited
https://huggingface.co/LLM360/AmberSafe
Amber
AmberSafe
Apache-2.0
LLM360, an initiative to fully open-source LLMs.
https://www.llm360.ai/index.html
November 2023
Availability
Base Model Data
data well-documented and openly available.
https://huggingface.co/datasets/LLM360/AmberDatasets
End User Model Data
RL and fine-tuning data shared and documented.
https://huggingface.co/datasets/WizardLM/WizardLM_evol_instruct_V2_196k
Base Model Weights
360 model checkpoints released.
https://huggingface.co/LLM360/Amber
End User Model Weights
Finetuned model available for download.
https://huggingface.co/LLM360/AmberChat
Training Code
amber-train repository includes code for training and finetuning.
https://github.com/LLM360/amber-train/tree/main
Documentation
Code Documentation
Code documented in helpful readme.md files but only partly inline.
https://github.com/LLM360
Hardware Architecture
Architecture described in preprint, but not all details documented.
https://arxiv.org/abs/2312.06550
Preprint
Preprint describes architecture, design choices, training and fine-tuning.
https://arxiv.org/abs/2312.06550
Paper
No peer-reviewed paper yet.
Modelcard
Model card doesn't specify use or limitations.
https://huggingface.co/LLM360/AmberChat
Datasheet
Concise description (better than most), but doesn't specify funders, purposes, representativeness, legal status as prescribed by datasheets industry standard.
https://huggingface.co/datasets/LLM360/AmberDatasets
Access
Package
No released package found.
API and Meta Prompts
Free Huggingface inference API.
https://huggingface.co/LLM360/AmberChat
Licenses
Everything licensed under Apache 2.0.
https://huggingface.co/LLM360/AmberChat
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