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liuw15/qwen3-8b-ziyon-nsfw-Q4_K_M-GGUF overview

liuw15/qwen3 8b ziyon nsfw Q4 K M GGUF This model was converted to GGUF format from liuw15/qwen3 8b ziyon nsfw https://huggingface.co/liuw15/qwen3 8b ziyon nsf…

transformersggufunslothllama-cppgguf-my-repotext-generationbase_model:liuw15/qwen3-8b-ziyon-nsfwbase_model:quantized:liuw15/qwen3-8b-ziyon-nsfwlicense:apache-2.0endpoints_compatibleregion:usconversationalnot-for-all-audiences

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

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text-generation
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Repository Files & Downloads

1 GGUF files detected
Direct downloads for local inference
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qwen3-8b-ziyon-nsfw-q4_k_m.ggufGGUFQ4_K_M4.68 GBDownload

Model Details

Model IDliuw15/qwen3-8b-ziyon-nsfw-Q4_K_M-GGUF
Authorliuw15
Pipelinetext-generation
Licenseapache-2.0
Base modelliuw15/qwen3-8b-ziyon-nsfw
Last modified2026-08-22T16:15:18.000Z

Model README

---

tags:

  • unsloth
  • llama-cpp
  • gguf-my-repo

library_name: transformers

license: apache-2.0

license_link: https://huggingface.co/Qwen/Qwen3-8B/blob/main/LICENSE

pipeline_tag: text-generation

base_model: liuw15/qwen3-8b-ziyon-nsfw

---

liuw15/qwen3-8b-ziyon-nsfw-Q4_K_M-GGUF

This model was converted to GGUF format from liuw15/qwen3-8b-ziyon-nsfw 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 liuw15/qwen3-8b-ziyon-nsfw-Q4_K_M-GGUF --hf-file qwen3-8b-ziyon-nsfw-q4_k_m.gguf -p "The meaning to life and the universe is"

Server:

llama-server --hf-repo liuw15/qwen3-8b-ziyon-nsfw-Q4_K_M-GGUF --hf-file qwen3-8b-ziyon-nsfw-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 liuw15/qwen3-8b-ziyon-nsfw-Q4_K_M-GGUF --hf-file qwen3-8b-ziyon-nsfw-q4_k_m.gguf -p "The meaning to life and the universe is"

or

./llama-server --hf-repo liuw15/qwen3-8b-ziyon-nsfw-Q4_K_M-GGUF --hf-file qwen3-8b-ziyon-nsfw-q4_k_m.gguf -c 2048

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