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This is a merge of [LongAlpaca-70B-lora](https://huggingface.co/Yukang/LongAlpaca-70B-lora) into lizpreciatior's [lzlv_70b_fp16_hf](https://huggingface.co/lizpreciatior/lzlv_70b_fp16_hf), and removing the extra row and pad token so that the vocabularies match.
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There is no additional fine-tuning. The resulting model seems to not be broken... you can test whether it is truly the original model + 32K capability (use linear rope scaling 8).
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[ChuckMcSneed](https://huggingface.co/ChuckMcSneed) did a benchmark [here](https://huggingface.co/grimulkan/lzlv-longLORA-70b-rope8-32k-fp16/discussions/2), indicating 30% degradation with 8x the context length.
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You could also try merging this with other models of longLORA descendency (like [Aurelian](https://huggingface.co/grimulkan/aurelian-v0.5-70b-rope8-32K-fp16)).
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A 6-bit EXL2 quantization is available [here](https://huggingface.co/grimulkan/lzlv-longLORA-70b-rope8-32k-6bpw-h8-exl2).
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This is a merge of [LongAlpaca-70B-lora](https://huggingface.co/Yukang/LongAlpaca-70B-lora) into lizpreciatior's [lzlv_70b_fp16_hf](https://huggingface.co/lizpreciatior/lzlv_70b_fp16_hf), and removing the extra row and pad token so that the vocabularies match.
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There is no additional fine-tuning. The resulting model seems to not be broken... you can test whether it is truly the original model + 32K capability (use linear rope scaling 8).
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[ChuckMcSneed](https://huggingface.co/ChuckMcSneed) did a benchmark [here](https://huggingface.co/grimulkan/lzlv-longLORA-70b-rope8-32k-fp16/discussions/2), indicating 30% degradation with 8x the context length.
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You could also try merging this with other models of longLORA descendency (like [Aurelian](https://huggingface.co/grimulkan/aurelian-v0.5-70b-rope8-32K-fp16)).
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A 6-bit EXL2 quantization is available [here](https://huggingface.co/grimulkan/lzlv-longLORA-70b-rope8-32k-6bpw-h8-exl2).
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