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Skills tagged: GGUF

Browse skills that share this tag.

  • llama-cpp - Run GGUF models locally with llama.cpp
    llama.cppGGUFquantizationHugging Face Hub

    ★ 92 · Updated 2026-09-09

    Runs local GGUF inference, selects quantizations, and discovers llama.cpp-compatible models and files on Hugging Face.

    ⚙ Run local GGUF inference⚙ Discover GGUF models on Hugging Face⚙ Select quantizations for hardware
  • gguf-quantization - GGUF Quantization for Efficient Model Inference
    GGUFQuantizationllama.cppCPU Inference

    ★ 0 · Updated 2026-06-30

    Convert and quantize models to GGUF format for efficient CPU/GPU inference

    ⚙ convert model to GGUF⚙ quantize GGUF model⚙ run model inference
  • llama-cpp - Local GGUF Inference & Model Discovery
    llama.cppGGUFQuantizationHugging Face Hub

    ★ 0 · Updated 2026-05-11

    Run local GGUF models and discover Hugging Face repositories for llama.cpp

    ⚙ run local models⚙ search Hugging Face Hub⚙ discover GGUF files
  • llama-cpp - Local GGUF Inference & HF Discovery
    llama.cppGGUFQuantizationHugging Face Hub

    ★ 17 · Updated 2026-05-11

    Local GGUF inference, quant selection, and Hugging Face Hub model discovery for llama.cpp

    ⚙ Run local models⚙ Search Hugging Face Hub⚙ Find GGUF files
  • llama-cpp - Local GGUF Model Inference
    GGUFLocal InferenceHugging FaceQuantization

    ★ 1 · Updated 2026-05-11

    Run GGUF models locally and discover models from Hugging Face Hub

    ⚙ discover Hugging Face repos⚙ download GGUF files⚙ run GGUF models locally
  • unsloth-finetuning - Fine-tune LLMs with Unsloth
    LLMfine-tuning4-bit quantizationLoRA

    ★ 602 · Updated 2026-03-26

    Fine-tune LLMs with Unsloth using 4-bit quantization and LoRA

    ⚙ load 4-bit quantized models⚙ configure LoRA parameters⚙ train on datasets
  • llama-cpp - llama.cpp Secondary LLM Inference Engine
    inferenceLLMGGUFLoRA

    ★ 18 · Updated 2026-03-10

    Secondary local LLM inference engine for running GGUF models directly, loading LoRA adapters, benchmarking, and custom model serving

    ⚙ run GGUF inference⚙ load LoRA adapter⚙ benchmark inference