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galahad-mamad/GambronAI-Persian-Q4_K_M-GGUF overview

galahad mamad/GambronAI Persian Q4 K M GGUF This model was converted to GGUF format from galahad mamad/GambronAI Persian https://huggingface.co/galahad mamad/G…

transformersggufpersianqeshmdialectfine-tunedllama-cppgguf-my-repotext-generationfadataset:custom-persian-dialectbase_model:galahad-mamad/GambronAI-Persianbase_model:quantized:galahad-mamad/GambronAI-Persianlicense:apache-2.0endpoints_compatibleregion:usconversational

Runs locally from ~4.36 GB disk (8 GB VRAM class GPUs with llama.cpp / guIDE).

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Pipeline
text-generation

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1 GGUF files detected
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Model Details

Model IDgalahad-mamad/GambronAI-Persian-Q4_K_M-GGUF
Authorgalahad-mamad
Pipelinetext-generation
Licenseapache-2.0
Base modelgalahad-mamad/GambronAI-Persian
Last modified2026-06-11T05:23:17.000Z

Model README

---

language:

  • fa

license: apache-2.0

base_model: galahad-mamad/GambronAI-Persian

tags:

  • persian
  • qeshm
  • dialect
  • fine-tuned
  • llama-cpp
  • gguf-my-repo

datasets:

  • custom-persian-dialect

metrics:

  • loss

library_name: transformers

pipeline_tag: text-generation

---

galahad-mamad/GambronAI-Persian-Q4_K_M-GGUF

This model was converted to GGUF format from galahad-mamad/GambronAI-Persian 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 galahad-mamad/GambronAI-Persian-Q4_K_M-GGUF --hf-file gambronai-persian-q4_k_m.gguf -p "The meaning to life and the universe is"

Server:

llama-server --hf-repo galahad-mamad/GambronAI-Persian-Q4_K_M-GGUF --hf-file gambronai-persian-q4_k_m.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 galahad-mamad/GambronAI-Persian-Q4_K_M-GGUF --hf-file gambronai-persian-q4_k_m.gguf -p "The meaning to life and the universe is"

or

./llama-server --hf-repo galahad-mamad/GambronAI-Persian-Q4_K_M-GGUF --hf-file gambronai-persian-q4_k_m.gguf -c 2048

Run galahad-mamad/GambronAI-Persian-Q4_K_M-GGUF with guIDE

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