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Joe57005/Marco-Nano-Instruct-Q4_0-GGUF overview

Joe57005/Marco Nano Instruct Q4 0 GGUF This model was converted to GGUF format from ATH MaaS/Marco Nano Instruct https://huggingface.co/ATH MaaS/Marco Nano Ins…

transformersggufmoemixture-of-expertsmultilingualupcyclingllama-cppgguf-my-repoenzhardeesfrkojapttriditnlplruvi

Runs locally from ~4.26 GB disk (8 GB VRAM class GPUs with llama.cpp / guIDE).

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Model Details

Model IDJoe57005/Marco-Nano-Instruct-Q4_0-GGUF
AuthorJoe57005
Pipeline
Licenseapache-2.0
Base modelATH-MaaS/Marco-Nano-Instruct
Last modified2026-07-08T23:05:02.000Z

Model README

---

license: apache-2.0

language:

  • en
  • zh
  • ar
  • de
  • es
  • fr
  • ko
  • ja
  • pt
  • tr
  • id
  • it
  • nl
  • pl
  • ru
  • vi
  • th
  • he
  • uk
  • ms
  • bn
  • cs
  • ur
  • kk
  • el
  • ro
  • hu
  • ne
  • az

library_name: transformers

tags:

  • moe
  • mixture-of-experts
  • multilingual
  • upcycling
  • llama-cpp
  • gguf-my-repo

datasets:

  • allenai/Dolci-Instruct-SFT
  • nvidia/Nemotron-Cascade-2-SFT-Data
  • nvidia/Nemotron-RL-instruction_following
  • nvidia/Nemotron-RL-instruction_following-structured_outputs
  • nvidia/Nemotron-RL-ReasoningGym-v1
  • nvidia/Nemotron-RL-knowledge-mcqa
  • nvidia/Nemotron-Cascade-RL-RLHF
  • BytedTsinghua-SIA/DAPO-Math-17k
  • Skywork/Skywork-OR1-RL-Data
  • nvidia/Nemotron-SFT-Multilingual-v1

base_model: ATH-MaaS/Marco-Nano-Instruct

---

Joe57005/Marco-Nano-Instruct-Q4_0-GGUF

This model was converted to GGUF format from ATH-MaaS/Marco-Nano-Instruct using llama.cpp via the ggml.ai's GGUF-my-repo space.

Refer to the original model card for more details on the model.

Use with llama.cpp

Install llama.cpp through brew (works on Mac and Linux)

brew install llama.cpp

Invoke the llama.cpp server or the CLI.

CLI:

llama-cli --hf-repo Joe57005/Marco-Nano-Instruct-Q4_0-GGUF --hf-file marco-nano-instruct-q4_0.gguf -p "The meaning to life and the universe is"

Server:

llama-server --hf-repo Joe57005/Marco-Nano-Instruct-Q4_0-GGUF --hf-file marco-nano-instruct-q4_0.gguf -c 2048

Note: You can also use this checkpoint directly through the usage steps listed in the Llama.cpp repo as well.

Step 1: Clone llama.cpp from GitHub.

git clone https://github.com/ggerganov/llama.cpp

Step 2: Move into the llama.cpp folder and build it with LLAMA_CURL=1 flag along with other hardware-specific flags (for ex: LLAMA_CUDA=1 for Nvidia GPUs on Linux).

cd llama.cpp && LLAMA_CURL=1 make

Step 3: Run inference through the main binary.

./llama-cli --hf-repo Joe57005/Marco-Nano-Instruct-Q4_0-GGUF --hf-file marco-nano-instruct-q4_0.gguf -p "The meaning to life and the universe is"

or

./llama-server --hf-repo Joe57005/Marco-Nano-Instruct-Q4_0-GGUF --hf-file marco-nano-instruct-q4_0.gguf -c 2048

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