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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?

Solar

by Upstage AI

HuggingFace profile says 'Solar is a great example of the progress enabled by open source.'
Text
Latest
https://huggingface.co/upstage/SOLAR-10.7B-Instruct-v1.0
Mistral-7B-v0.1
SOLAR-10.7B-Instruct-v1.0
Meta Community License and CC-BY-NC-4.0
Korean venture
https://en.upstage.ai/
December 2023
Availability
Base Model Data
Mistral has not disclosed anything about its training data.
https://huggingface.co/mistralai/Mistral-7B-v0.1/discussions/8
End User Model Data
No RLHF datasets specified or shared, docs say 'Orca-style dataset, Alpaca-style dataset'
Base Model Weights
Weights available through HuggingFace.
https://huggingface.co/mistralai/Mistral-7B-v0.1
End User Model Weights
Finetuned checkpoints only shared through CC-BY-NC
https://huggingface.co/upstage/SOLAR-10.7B-Instruct-v1.0
Training Code
No code repository found
Documentation
Code Documentation
HuggingFace code only comprises configuration json; no documentation available.
Hardware Architecture
Precise architecture, training, fine-tuning procedures not given.
Preprint
No preprint or any form of scientific documentation found.
Paper
No peer-reviewed paper found
Modelcard
HuggingFace model provides partial information.
https://huggingface.co/upstage/SOLAR-10.7B-Instruct-v1.0
Datasheet
Datasheet not provided.
Access
Package
Model available on Ollama.
https://ollama.com/library/solar
API and Meta Prompts
API only available by signing up for 'private LLM' service
Licenses
Meta Community License for base model, and CC-BY-NC 4.0 for fine-tuned model weights
https://huggingface.co/upstage/SOLAR-10.7B-Instruct-v1.0#license
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