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README.md
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## Benchmarking results
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You can find results for more tasks and models in this [spreadsheet](https://docs.google.com/spreadsheets/d/1qGzimBE8F896p1m7_yWHnjyGX7kpEAeyaT1h2iTbNzE/edit?usp=sharing). In this detailed results, we show that our model can retain the original Llama-3's general LM performance (on tasks selected by the [HF Open LLM Leaderboard v1](https://huggingface.co/spaces/open-llm-leaderboard-old/open_llm_leaderboard)). This is non-trivial in long-context fine-tuning and requires a careful selection of the fine-tuning data mixture and the training configurations.
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## Benchmarking results
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64K result:
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512K result:
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You can find results for more tasks and models in this [spreadsheet](https://docs.google.com/spreadsheets/d/1qGzimBE8F896p1m7_yWHnjyGX7kpEAeyaT1h2iTbNzE/edit?usp=sharing). In this detailed results, we show that our model can retain the original Llama-3's general LM performance (on tasks selected by the [HF Open LLM Leaderboard v1](https://huggingface.co/spaces/open-llm-leaderboard-old/open_llm_leaderboard)). This is non-trivial in long-context fine-tuning and requires a careful selection of the fine-tuning data mixture and the training configurations.
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