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README.md
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This model was converted to GGUF format from [`nvidia/AceInstruct-7B`](https://huggingface.co/nvidia/AceInstruct-7B) using llama.cpp via the ggml.ai's [GGUF-my-repo](https://huggingface.co/spaces/ggml-org/gguf-my-repo) space.
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Refer to the [original model card](https://huggingface.co/nvidia/AceInstruct-7B) for more details on the model.
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## Use with llama.cpp
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Install llama.cpp through brew (works on Mac and Linux)
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This model was converted to GGUF format from [`nvidia/AceInstruct-7B`](https://huggingface.co/nvidia/AceInstruct-7B) using llama.cpp via the ggml.ai's [GGUF-my-repo](https://huggingface.co/spaces/ggml-org/gguf-my-repo) space.
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Refer to the [original model card](https://huggingface.co/nvidia/AceInstruct-7B) for more details on the model.
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---
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We introduce AceInstruct, a family of advanced SFT models for coding,
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mathematics, and general-purpose tasks. The AceInstruct family, which
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includes AceInstruct-1.5B, 7B, and 72B, is Improved using Qwen.
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These models are fine-tuned on Qwen2.5-Base using general SFT datasets. These same datasets are also used in the training of AceMath-Instruct.
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Different from AceMath-Instruct which is specialized for math
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questions, AceInstruct is versatile and can be applied to a wide range
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of domains. Benchmark evaluations across coding, mathematics, and
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general knowledge tasks demonstrate that AceInstruct delivers
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performance comparable to Qwen2.5-Instruct.
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For more information about AceInstruct, check our website and paper.
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---
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## Use with llama.cpp
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Install llama.cpp through brew (works on Mac and Linux)
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