Hanuman2/mergekit-slerp-xwepacy-Q4_K_M-GGUF overview
Hanuman2/mergekit slerp xwepacy Q4 K M GGUF This model was converted to GGUF format from Hanuman2/mergekit slerp xwepacy https://huggingface.co/Hanuman2/mergek…
Runs locally from ~4.07 GB disk (8 GB VRAM class GPUs with llama.cpp / guIDE).
Repository Files & Downloads
| File | Type | Quantization | Size | Link |
|---|---|---|---|---|
| mergekit-slerp-xwepacy-q4_k_m.gguf | GGUF | Q4_K_M | 4.07 GB | Download |
Model Details
Model README
---
base_model: Hanuman2/mergekit-slerp-xwepacy
library_name: transformers
tags:
- mergekit
- merge
- llama-cpp
- gguf-my-repo
---
Hanuman2/mergekit-slerp-xwepacy-Q4_K_M-GGUF
This model was converted to GGUF format from Hanuman2/mergekit-slerp-xwepacy 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 Hanuman2/mergekit-slerp-xwepacy-Q4_K_M-GGUF --hf-file mergekit-slerp-xwepacy-q4_k_m.gguf -p "The meaning to life and the universe is"
Server:
llama-server --hf-repo Hanuman2/mergekit-slerp-xwepacy-Q4_K_M-GGUF --hf-file mergekit-slerp-xwepacy-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 Hanuman2/mergekit-slerp-xwepacy-Q4_K_M-GGUF --hf-file mergekit-slerp-xwepacy-q4_k_m.gguf -p "The meaning to life and the universe is"
or
./llama-server --hf-repo Hanuman2/mergekit-slerp-xwepacy-Q4_K_M-GGUF --hf-file mergekit-slerp-xwepacy-q4_k_m.gguf -c 2048Run Hanuman2/mergekit-slerp-xwepacy-Q4_K_M-GGUF with guIDE
Download guIDE — the AI-native code editor with local LLM inference and 69 built-in tools.
Source: Hugging Face · Compare models