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Fabio2000/Jinx-Qwen3-8B-Q4_K_M-GGUF overview

Fabio2000/Jinx Qwen3 8B Q4 K M GGUF This model was converted to GGUF format from Jinx org/Jinx Qwen3 8B https://huggingface.co/Jinx org/Jinx Qwen3 8B using lla…

transformersggufvllmllama-cppgguf-my-repotext-generationbase_model:Jinx-org/Jinx-Qwen3-8Bbase_model:quantized:Jinx-org/Jinx-Qwen3-8Blicense:apache-2.0endpoints_compatibleregion:usconversational

Runs locally from ~4.68 GB disk (8 GB VRAM class GPUs with llama.cpp / guIDE).

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1 GGUF files detected
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Model Details

Model IDFabio2000/Jinx-Qwen3-8B-Q4_K_M-GGUF
AuthorFabio2000
Pipelinetext-generation
Licenseapache-2.0
Base modelJinx-org/Jinx-Qwen3-8B
Last modified2026-06-24T23:21:38.000Z

Model README

---

library_name: transformers

license: apache-2.0

pipeline_tag: text-generation

base_model: Jinx-org/Jinx-Qwen3-8B

tags:

  • vllm
  • llama-cpp
  • gguf-my-repo

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If you do not agree with any part of this Agreement, do not request or use the Model.

2. Nature of the Model & Risk Notice

The Model is trained using large-scale machine learning techniques and may generate

inaccurate, false, offensive, violent, sexual, discriminatory, politically sensitive,

or otherwise uncontrolled content.

The Model does not guarantee the accuracy, completeness, or legality of any generated

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---

Fabio2000/Jinx-Qwen3-8B-Q4_K_M-GGUF

This model was converted to GGUF format from Jinx-org/Jinx-Qwen3-8B 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 Fabio2000/Jinx-Qwen3-8B-Q4_K_M-GGUF --hf-file jinx-qwen3-8b-q4_k_m.gguf -p "The meaning to life and the universe is"

Server:

llama-server --hf-repo Fabio2000/Jinx-Qwen3-8B-Q4_K_M-GGUF --hf-file jinx-qwen3-8b-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 Fabio2000/Jinx-Qwen3-8B-Q4_K_M-GGUF --hf-file jinx-qwen3-8b-q4_k_m.gguf -p "The meaning to life and the universe is"

or

./llama-server --hf-repo Fabio2000/Jinx-Qwen3-8B-Q4_K_M-GGUF --hf-file jinx-qwen3-8b-q4_k_m.gguf -c 2048

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