--- base_model: knifeayumu/Cydonia-v1.3-Magnum-v4-22B library_name: transformers tags: - mergekit - merge - llama-cpp - gguf-my-repo license: other license_name: mrl inference: false license_link: https://mistral.ai/licenses/MRL-0.1.md --- # Triangle104/Cydonia-v1.3-Magnum-v4-22B-Q4_K_S-GGUF This model was converted to GGUF format from [`knifeayumu/Cydonia-v1.3-Magnum-v4-22B`](https://huggingface.co/knifeayumu/Cydonia-v1.3-Magnum-v4-22B) using llama.cpp via the ggml.ai's [GGUF-my-repo](https://huggingface.co/spaces/ggml-org/gguf-my-repo) space. Refer to the [original model card](https://huggingface.co/knifeayumu/Cydonia-v1.3-Magnum-v4-22B) for more details on the model. --- Model details: - The Drummer becomes hornier (again) Recipe based on knifeayumu/Cydonia-v1.2-Magnum-v4-22B but uses TheDrummer/Cydonia-22B-v1.3 as the base. Yes, MortalWombat. I'm gonna use your parameters as long as I can! This is a merge of pre-trained language models created using mergekit. Merge Method - This model was merged using the SLERP merge method. Models Merged - The following models were included in the merge: TheDrummer/Cydonia-22B-v1.3 anthracite-org/magnum-v4-22b Configuration - The following YAML configuration was used to produce this model: models: - model: TheDrummer/Cydonia-22B-v1.3 - model: anthracite-org/magnum-v4-22b merge_method: slerp base_model: TheDrummer/Cydonia-22B-v1.3 parameters: t: [0.1, 0.3, 0.6, 0.3, 0.1] dtype: bfloat16 --- ## Use with llama.cpp Install llama.cpp through brew (works on Mac and Linux) ```bash brew install llama.cpp ``` Invoke the llama.cpp server or the CLI. ### CLI: ```bash llama-cli --hf-repo Triangle104/Cydonia-v1.3-Magnum-v4-22B-Q4_K_S-GGUF --hf-file cydonia-v1.3-magnum-v4-22b-q4_k_s.gguf -p "The meaning to life and the universe is" ``` ### Server: ```bash llama-server --hf-repo Triangle104/Cydonia-v1.3-Magnum-v4-22B-Q4_K_S-GGUF --hf-file cydonia-v1.3-magnum-v4-22b-q4_k_s.gguf -c 2048 ``` Note: You can also use this checkpoint directly through the [usage steps](https://github.com/ggerganov/llama.cpp?tab=readme-ov-file#usage) 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/Cydonia-v1.3-Magnum-v4-22B-Q4_K_S-GGUF --hf-file cydonia-v1.3-magnum-v4-22b-q4_k_s.gguf -p "The meaning to life and the universe is" ``` or ``` ./llama-server --hf-repo Triangle104/Cydonia-v1.3-Magnum-v4-22B-Q4_K_S-GGUF --hf-file cydonia-v1.3-magnum-v4-22b-q4_k_s.gguf -c 2048 ```