README.md

metadata

license: apache-2.0
base_model: FINAL-Bench/Darwin-4B-Genesis
tags:
  - merge
  - evolutionary-merge
  - darwin
  - darwin-v6
  - model-mri
  - cross-architecture
  - ffn-crossbreed
  - cma-es
  - hybrid-vigor
  - transformer-mamba
  - reasoning
  - gemma4
  - qwen3.5
  - gated-deltanet
  - korean
  - multilingual
  - gpqa
  - open-source
  - apache-2.0
  - world-first
  - llama-cpp
  - gguf-my-repo
language:
  - ko
  - en
  - zh
  - ja
  - de
  - fr
  - es
pipeline_tag: text-generation
model-index:
  - name: Darwin-4B-Genesis
    results:
      - task:
          type: text-generation
          name: Korean Cultural Understanding
        dataset:
          name: CLIcK
          type: EunsuKim/CLIcK
        metrics:
          - type: accuracy
            value: 92
            name: Accuracy
            verified: false
      - task:
          type: text-generation
          name: Multi-Step Reasoning
        dataset:
          name: MuSR
          type: TAUR-Lab/MuSR
        metrics:
          - type: accuracy
            value: 70
            name: Accuracy
            verified: false

Cheuv/Darwin-4B-Genesis-Q8_0-GGUF

This model was converted to GGUF format from FINAL-Bench/Darwin-4B-Genesis 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 Cheuv/Darwin-4B-Genesis-Q8_0-GGUF --hf-file darwin-4b-genesis-q8_0.gguf -p "The meaning to life and the universe is"

Server:

llama-server --hf-repo Cheuv/Darwin-4B-Genesis-Q8_0-GGUF --hf-file darwin-4b-genesis-q8_0.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 Cheuv/Darwin-4B-Genesis-Q8_0-GGUF --hf-file darwin-4b-genesis-q8_0.gguf -p "The meaning to life and the universe is"

or

./llama-server --hf-repo Cheuv/Darwin-4B-Genesis-Q8_0-GGUF --hf-file darwin-4b-genesis-q8_0.gguf -c 2048