Triangle104/Harbinger-24B-Q3_K_M-GGUF

This model was converted to GGUF format from LatitudeGames/Harbinger-24B using llama.cpp via the ggml.ai's GGUF-my-repo space. Refer to the original model card for more details on the model.

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Like our Wayfarer line of finetunes, Harbinger-24B was designed for immersive adventures and other stories where consequences feel real and every decision matters. Training focused on enhancing instruction following, improving mid-sequence continuation, and strengthening narrative coherence over long sequences of outputs without user intervention. The same DPO (direct preference optimization) techniques used in our Muse model were applied to Harbinger, resulting in polished outputs with fewer clichés, repetitive patterns, and other common artifacts.

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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 Triangle104/Harbinger-24B-Q3_K_M-GGUF --hf-file harbinger-24b-q3_k_m.gguf -p "The meaning to life and the universe is"

Server:

llama-server --hf-repo Triangle104/Harbinger-24B-Q3_K_M-GGUF --hf-file harbinger-24b-q3_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 Triangle104/Harbinger-24B-Q3_K_M-GGUF --hf-file harbinger-24b-q3_k_m.gguf -p "The meaning to life and the universe is"

or

./llama-server --hf-repo Triangle104/Harbinger-24B-Q3_K_M-GGUF --hf-file harbinger-24b-q3_k_m.gguf -c 2048