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  license: apache-2.0
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  ---
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- Converted using ggerganov/ggml's "stablelm" conversion script and quantization code as of [commit 05f3079](https://github.com/ggerganov/ggml/tree/05f307971862b83df12fada0c42ee027ba5a82b5/examples/stablelm) (2023-04-20). Should be compatible with KoboldCpp.
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- These conversions are based off of [the updated Pythia Deduped checkpoints](https://huggingface.co/models?sort=downloads&search=pythia+deduped), not [the original v0 trainings](https://huggingface.co/models?search=pythia%20deduped%20v0).
 
 
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  **NOTE:** pythia-70m-deduped gave garbage output in my testing.
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  # RAM USAGE (koboldcpp):
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- Model | Loaded RAM usage
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  :--:|:--:
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  ggml-pythia-70m-deduped-q4_3.bin | 121.2 MiB
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  ggml-pythia-160m-deduped-q4_3.bin | 225.2 MiB
 
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  license: apache-2.0
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  ---
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+ Converted using ggerganov/ggml's "stablelm" conversion script and quantization code as of [commit 05f3079](https://github.com/ggerganov/ggml/tree/05f307971862b83df12fada0c42ee027ba5a82b5/examples/stablelm) (2023-04-20).
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+ These conversions are based off of the updated Pythia Deduped checkpoints, not the original v0 trainings.
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+
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+ Should be compatible with KoboldCpp. Perfect if you want to run them on low-end devices like a phone or Raspberry Pi.
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  **NOTE:** pythia-70m-deduped gave garbage output in my testing.
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  # RAM USAGE (koboldcpp):
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+ Model | Loaded RAM
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  :--:|:--:
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  ggml-pythia-70m-deduped-q4_3.bin | 121.2 MiB
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  ggml-pythia-160m-deduped-q4_3.bin | 225.2 MiB