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chibigon9/MetaMath-Qwen2.5-0.5b-PRM-Q8_0-GGUF overview

license: apache 2.0 base model: rawsh/MetaMath Qwen2.5 0.5b PRM tags: axolotl generated from trainer llama cpp gguf my repo language: zho eng fra spa por deu i…

ggufaxolotlgenerated_from_trainerllama-cppgguf-my-repozhoengfraspapordeuitarusjpnkorviethaarabase_model:rawsh/MetaMath-Qwen2.5-0.5b-PRMbase_model:quantized:rawsh/MetaMath-Qwen2.5-0.5b-PRMlicense:apache-2.0endpoints_compatibleregion:usconversational

Runs locally from ~506.5 MB disk (4 GB VRAM class GPUs with llama.cpp / guIDE).

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Repository Files & Downloads

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metamath-qwen2.5-0.5b-prm-q8_0.ggufGGUFQ8_0506.5 MBDownload

Model Details

Model IDchibigon9/MetaMath-Qwen2.5-0.5b-PRM-Q8_0-GGUF
Authorchibigon9
Pipeline
Licenseapache-2.0
Base modelrawsh/MetaMath-Qwen2.5-0.5b-PRM
Last modified2026-07-19T02:56:44.000Z

Model README

---

license: apache-2.0

base_model: rawsh/MetaMath-Qwen2.5-0.5b-PRM

tags:

  • axolotl
  • generated_from_trainer
  • llama-cpp
  • gguf-my-repo

language:

  • zho
  • eng
  • fra
  • spa
  • por
  • deu
  • ita
  • rus
  • jpn
  • kor
  • vie
  • tha
  • ara

model-index:

  • name: MetaMath-Qwen2.5-0.5b-PRM

results: []

---

chibigon9/MetaMath-Qwen2.5-0.5b-PRM-Q8_0-GGUF

This model was converted to GGUF format from rawsh/MetaMath-Qwen2.5-0.5b-PRM 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 chibigon9/MetaMath-Qwen2.5-0.5b-PRM-Q8_0-GGUF --hf-file metamath-qwen2.5-0.5b-prm-q8_0.gguf -p "The meaning to life and the universe is"

Server:

llama-server --hf-repo chibigon9/MetaMath-Qwen2.5-0.5b-PRM-Q8_0-GGUF --hf-file metamath-qwen2.5-0.5b-prm-q8_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 chibigon9/MetaMath-Qwen2.5-0.5b-PRM-Q8_0-GGUF --hf-file metamath-qwen2.5-0.5b-prm-q8_0.gguf -p "The meaning to life and the universe is"

or

./llama-server --hf-repo chibigon9/MetaMath-Qwen2.5-0.5b-PRM-Q8_0-GGUF --hf-file metamath-qwen2.5-0.5b-prm-q8_0.gguf -c 2048

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