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This model was converted to GGUF format from [`katanemo/Arch-Function-Chat-1.5B`](https://huggingface.co/katanemo/Arch-Function-Chat-1.5B) 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/katanemo/Arch-Function-Chat-1.5B) 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 [`katanemo/Arch-Function-Chat-1.5B`](https://huggingface.co/katanemo/Arch-Function-Chat-1.5B) 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/katanemo/Arch-Function-Chat-1.5B) for more details on the model.
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The Arch-Function-Chat collection builds upon the Katanemo's Arch-Function
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collection by extending its capabilities beyond function calling. This
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new collection maintains the state-of-the-art(SOTA) function calling
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performance of the original collection while adding powerful new
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features that make it even more versatile in real-world applications.
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In addition to function calling capabilities, this collection now offers:
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-Clarify & refine: Generates natural follow-up questions to collect missing information for function calling
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-Interpret & respond: Provides human-friendly responses based on function execution results
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-Context management: Mantains context in complex multi-turn interactions
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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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