Added Models.
Browse filesI fucking love breakcore.
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- README.md +48 -0
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README.md
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# Planck-OpenLAiNN-10M-GGUF 🤗
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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!~
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These are the GGUF quants of the models. For the original models, you can find them [here](https://huggingface.co/UUFO-Aigis/Planck-OpenLAiNN-10M).
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## Models Overview
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- **Panck-OpenLAiNN-10M**: A Truely Tiny model with just 10 Million parameters, this is probably boarderline useless, but it *IS* functional.
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- **Panck-OpenLAiNN-25M**: The second smallest model, 25 million parameters, it's not that much better.
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- **Panck-OpenLAiNN-50M**: Surprisingly smart, it's 50 Million parameters and could potentially maybe, Possibly even be useful ;)
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- **Panck-OpenLAiNN-75M**: The current *""heavy""* weight of the Plank-OpenLAiNN Models.
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## Pretraining Details
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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.
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## Other information:
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- **Compatibility**: Built to be compatible with existing projects that use LLAMA 2's tokenizer and architecture.
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- **Ease of Use**: No need to reinvent the wheel. These models are ready to be plugged into your applications.
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- **Open Source**: Fully open source, so you can tweak, tune, and twist them to your heart's content.
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# Benchy
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| Tasks | Value | |Stderr|
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|--------------|------:|---|-----:|
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|arc_challenge | 0.1766|± |0.0111|
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|arc_easy | 0.3144|± |0.0095|
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|boolq | 0.5847|± |0.0086|
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|hellaswag | 0.2622|± |0.0044|
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|lambada_openai| 0.0047|± |0.0009| # Yes, really
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|piqa | 0.5718|± |0.0115|
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|winogrande | 0.4957|± |0.0141|
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## Future Plans
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- **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.
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- **New architecture**: This is still up in the air and I'm still developing it, things are going well and I'll post updates.
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- **Paper**: A detailed paper or training data will be posted at some point.
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## Credit Where Credit's Due
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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 🤗
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## Contact
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If you have questions, Please reach out to me at [email protected]
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<p align="center">
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<img src="UUFO.png" alt="U.U.F.O Research Logo" width="250"/>
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</p>
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UUFO.png
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