Planck-OpenLAiNN-10M-GGUF 🤗

Hey there fellow researchers, developers, and AI enthusiasts! Today I'm releasing a new family of Models, Planck LAiNN, These are probably some of the smallest LLMs that are on HF. They aren't super useful but it was a fun expierment!~

These are the GGUF quants of the models. For the original models, you can find them here.

Models Overview

Panck-OpenLAiNN-10M: A Truely Tiny model with just 10 Million parameters, this is probably boarderline useless, but it IS functional.
Panck-OpenLAiNN-25M: The second smallest model, 25 million parameters, it's not that much better.
Panck-OpenLAiNN-50M: Surprisingly smart, it's 50 Million parameters and could potentially maybe, Possibly even be useful ;)
Panck-OpenLAiNN-75M: The current ""heavy"" weight of the Plank-OpenLAiNN Models.

Pretraining Details

Plank-OpenLAiNN was trained on 32B tokens of the Fineweb dataset, it's the same one that was used for the Pico-LAiNN family of models. The model was pretrained with a context length of 1024 tokens.

Other information:

Compatibility: Built to be compatible with existing projects that use LLAMA 2's tokenizer and architecture.
Ease of Use: No need to reinvent the wheel. These models are ready to be plugged into your applications.
Open Source: Fully open source, so you can tweak, tune, and twist them to your heart's content.

Benchy

Tasks	Value		Stderr
arc_challenge	0.1766	±	0.0111
arc_easy	0.3144	±	0.0095
boolq	0.5847	±	0.0086
hellaswag	0.2622	±	0.0044
lambada_openai	0.0047	±	0.0009
piqa	0.5718	±	0.0115
winogrande	0.4957	±	0.0141

Future Plans

More Models: I'm currenetly training the bigger siblings of Pico-OpenLAiNN, including a 1B parameter version and beyond. 2-4 Billion parameter versions are planned. These will be Released as OpenLAiNN.
New architecture: This is still up in the air and I'm still developing it, things are going well and I'll post updates.
Paper: A detailed paper or training data will be posted at some point.

Credit Where Credit's Due

If you find these models useful and decide to use these models, a link to this repository would be highly appreciated. I am a one man show running this and I'm doing this for free, Thanks 🤗

Contact

If you have questions, Please reach out to me at urlsys32dll@gmail.com

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