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license: apache-2.0
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**NOTE:** Tested with KoboldCpp.
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**2023-04-20:** Converted using ggerganov/ggml's "stablelm" conversion script and quantization code as of [commit 05f3079](https://github.com/ggerganov/ggml/tree/05f307971862b83df12fada0c42ee027ba5a82b5/examples/stablelm).
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**2023-04-30:** Converted using ggerganov/ggml's "stablelm" conversion script and quantization code as of [commit 5dd92f4](https://github.com/ggerganov/ggml/tree/5dd92f421ee44f18b8fde0afbf5ca8fc7bf93841/examples/stablelm).
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These conversions are based off of the updated Pythia Deduped checkpoints, not the original v0 trainings.
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license: apache-2.0
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# **NOTE:** Tested with KoboldCpp.
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## (I can't promise that it will work with other frontends, if at all. Use at your own risk!)
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**2023-04-20:** Includes q4_3 versions of all Pythia Deduped models. Converted using ggerganov/ggml's "stablelm" conversion script and quantization code as of [commit 05f3079](https://github.com/ggerganov/ggml/tree/05f307971862b83df12fada0c42ee027ba5a82b5/examples/stablelm).
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**2023-04-30:** Includes q5_0, q5_1, and q8_0 versions of Pythia Deduped models up to 2.8B. Converted using ggerganov/ggml's "stablelm" conversion script and quantization code as of [commit 5dd92f4](https://github.com/ggerganov/ggml/tree/5dd92f421ee44f18b8fde0afbf5ca8fc7bf93841/examples/stablelm).
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**2023-05-06:** Includes q4_0 and q4_2 versions of Pythia Deduped models up to 2.8B. Converted using ggerganov/ggml's "stablelm" conversion script and quantization code as of [commit ff6e03c](https://github.com/ggerganov/ggml/tree/ff6e03cbcd9bf6e9fa41d49f2495c042efae4dc6/examples/stablelm).
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They're separated by date and commit so it's easier to track any breaking changes. The last two go up to 2.8B because it's time-consuming (and unreliable even overnight) for me to upload q4_0, q5_0, q5_1, and q8_0 for the 6.9B and 12B conversions. If you have the hardware for a 7B+ model, I would recommend the currently-training [OpenLLaMA 7B](https://huggingface.co/vihangd/open_llama_7b_300bt_ggml).
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These conversions are based off of the updated Pythia Deduped checkpoints, not the original v0 trainings.
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