Triangle104/The-Omega-Directive-M-8B-v1.0-Q5_K_S-GGUF

This model was converted to GGUF format from ReadyArt/The-Omega-Directive-M-8B-v1.0 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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This evolution of Forgotten-Safeword delivers coherent depravity with unprecedented immersion:

🧬 Expanded 22M Token Dataset - Incorporating 90 erotic novels and 6,496 kink scenarios

⚡ Optimized Architecture - Smoother training curve yields more intelligent outputs

💎 Balanced Depravity - Retains Forgotten-Safeword's edge while reducing jarring inconsistencies

📜 Enhanced Character Piloting - Characters exhibit more nuanced personalities and motivations

🌹 Unexpected Depth - Occasionally surprises with profound insights amidst the debauchery

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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/The-Omega-Directive-M-8B-v1.0-Q5_K_S-GGUF --hf-file the-omega-directive-m-8b-v1.0-q5_k_s.gguf -p "The meaning to life and the universe is"

Server:

llama-server --hf-repo Triangle104/The-Omega-Directive-M-8B-v1.0-Q5_K_S-GGUF --hf-file the-omega-directive-m-8b-v1.0-q5_k_s.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/The-Omega-Directive-M-8B-v1.0-Q5_K_S-GGUF --hf-file the-omega-directive-m-8b-v1.0-q5_k_s.gguf -p "The meaning to life and the universe is"

or

./llama-server --hf-repo Triangle104/The-Omega-Directive-M-8B-v1.0-Q5_K_S-GGUF --hf-file the-omega-directive-m-8b-v1.0-q5_k_s.gguf -c 2048