GraySoft
Projects Models Compare Cloud benchmarks FAQ Download guIDE →
Model Intelligence Sheet

pedrojlucas/gwen-retuned-literato-Q4_K_M-GGUF overview

pedrojlucas/gwen retuned literato Q4 K M GGUF This model was converted to GGUF format from pedrojlucas/gwen retuned literato https://huggingface.co/pedrojlucas…

ggufllama-cppgguf-my-repobase_model:pedrojlucas/gwen-retuned-literatobase_model:quantized:pedrojlucas/gwen-retuned-literatolicense:unlicenseendpoints_compatibleregion:us

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

Downloads
0
Likes
0
Pipeline

Repository Files & Downloads

1 GGUF files detected
Direct downloads for local inference
FileTypeQuantizationSizeLink
gwen-retuned-literato-q4_k_m.ggufGGUFQ4_K_M4.36 GBDownload

Model Details

Model IDpedrojlucas/gwen-retuned-literato-Q4_K_M-GGUF
Authorpedrojlucas
Pipeline
Licenseunlicense
Base modelpedrojlucas/gwen-retuned-literato
Last modified2026-08-14T16:38:02.000Z

Model README

---

license: unlicense

tags:

  • llama-cpp
  • gguf-my-repo

base_model: pedrojlucas/gwen-retuned-literato

---

pedrojlucas/gwen-retuned-literato-Q4_K_M-GGUF

This model was converted to GGUF format from pedrojlucas/gwen-retuned-literato 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 pedrojlucas/gwen-retuned-literato-Q4_K_M-GGUF --hf-file gwen-retuned-literato-q4_k_m.gguf -p "The meaning to life and the universe is"

Server:

llama-server --hf-repo pedrojlucas/gwen-retuned-literato-Q4_K_M-GGUF --hf-file gwen-retuned-literato-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 pedrojlucas/gwen-retuned-literato-Q4_K_M-GGUF --hf-file gwen-retuned-literato-q4_k_m.gguf -p "The meaning to life and the universe is"

or

./llama-server --hf-repo pedrojlucas/gwen-retuned-literato-Q4_K_M-GGUF --hf-file gwen-retuned-literato-q4_k_m.gguf -c 2048

Run pedrojlucas/gwen-retuned-literato-Q4_K_M-GGUF with guIDE

Download guIDE — the AI-native code editor with local LLM inference and 69 built-in tools.

Download guIDE → · Browse 524k+ models · Compare models

Source: Hugging Face · Compare models