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README.md
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## Support
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To run inference on this model, you'll need to use Aphrodite, vLLM or EXL2/tabbyAPI, as llama.cpp hasn't yet merged the required pull request to fix the llama3.1 rope_freqs issue with custom head dimensions.
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However, you can work around this by quantizing the model yourself to create a functional GGUF file. Note that until [this PR](https://github.com/ggerganov/llama.cpp/pull/9141) is merged, the context will be limited to 8k tokens.
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1. Remove the `"rope_scaling": {}` entry from `config.json`
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2. Change `"max_position_embeddings"` to `8192` in `config.json`
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These modifications should allow you to use the model with llama.cpp, albeit with the mentioned context limitation
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## axolotl config
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## Support
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Upstream support has been merged, so these quants work out of the box now!
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<details><summary>old instructions before PR</summary>
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To run inference on this model, you'll need to use Aphrodite, vLLM or EXL2/tabbyAPI, as llama.cpp hasn't yet merged the required pull request to fix the llama3.1 rope_freqs issue with custom head dimensions.
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However, you can work around this by quantizing the model yourself to create a functional GGUF file. Note that until [this PR](https://github.com/ggerganov/llama.cpp/pull/9141) is merged, the context will be limited to 8k tokens.
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1. Remove the `"rope_scaling": {}` entry from `config.json`
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2. Change `"max_position_embeddings"` to `8192` in `config.json`
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These modifications should allow you to use the model with llama.cpp, albeit with the mentioned context limitation.</strike>
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</details><br>
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## axolotl config
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