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MR-CODESPIKE/Qwen2.5-3B-Instruct-GGUF-Q4_K_M
Qwen2.5-3B-Instruct-GGUF-Q4_K_M is a machine learning model from MR-CODESPIKE. Use it for the machine learning task on the model card, and read the license before you ship it in a product.
This repository publishes a GGUF-format, Q4KM quantized artifact identified as a Qwen2.5 3B Instruct model. The repository is intended for local inference engines that support GGUF, such as llama.cpp-compatible runtimes.
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From the Hugging Face model README
This repository publishes a GGUF-format, Q4_K_M quantized artifact identified as a Qwen2.5 3B Instruct model. The repository is intended for local inference engines that support GGUF, such as llama.cpp-compatible runtimes.
Use this checkpoint for local experimentation, offline assistants, and resource-constrained inference. It is not a guarantee of factual accuracy, safety, or suitability for high-impact decisions. Review the upstream Qwen license and model-card terms before redistribution or commercial use.
pip install llama-cpp-python
Then load the repository's GGUF file using the runtime's model-path option and configure a chat completion prompt according to the upstream Qwen2.5 Instruct template. Exact context length, GPU offload, and performance depend on the runtime and hardware.
The Q4_K_M suffix describes the quantization variant. For reliable comparisons, record the runtime version, context length, sampling parameters, hardware, and the exact file revision. Do not assume that a quantized checkpoint has the same output quality or memory requirements as the original full-precision model.