This repository contains GGUF quantized versions of the Phi-4-mini-instruct model. Multiple quantization levels (Q2_K through Q8_0) are provided for different performance and memory trade-offs. The models are optimized for local inference using tools like llama.cpp.
Phi 4 Mini Instruct sits in PulseGate's Foundation models & chat category. It focuses on running lightweight instruction-tuned language models efficiently on consumer hardware using quantized GGUF files. It is built as an open-source project for developers. Phi 4 Mini Instruct is open source under the MIT license. Phi 4 Mini Instruct is available on the web, the command line, and API.
Behind Phi 4 Mini Instruct is MaziyarPanahi, and it first shipped in 2023. Development happens publicly on GitHub with 122.3k stars and 1.2k commits in the last 90 days. It operates in a well-populated space: PulseGate tracks 7 similar projects. Among its 3 catalogued features are Quantized Models, Instruct Tuning, and GGUF Format.
Summary written by a language model from the project’s public pages.
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