--- base_model: ClaudioItaly/Neithabet-9G library_name: transformers tags: - mergekit - merge - llama-cpp - gguf-my-repo --- # Triangle104/Neithabet-9G-Q8_0-GGUF This model was converted to GGUF format from [`ClaudioItaly/Neithabet-9G`](https://huggingface.co/ClaudioItaly/Neithabet-9G) 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/ClaudioItaly/Neithabet-9G) for more details on the model. --- This is a merge of pre-trained language models created using [mergekit](https://github.com/cg123/mergekit). ## Merge Details ### Merge Method This model was merged using the SLERP merge method. ### Models Merged The following models were included in the merge: * [ifable/gemma-2-Ifable-9B](https://huggingface.co/ifable/gemma-2-Ifable-9B) * [lemon07r/Gemma-2-Ataraxy-9B](https://huggingface.co/lemon07r/Gemma-2-Ataraxy-9B) ### Configuration The following YAML configuration was used to produce this model: ```yaml models: - model: lemon07r/Gemma-2-Ataraxy-9B - model: ifable/gemma-2-Ifable-9B merge_method: slerp tokenizer_merge_method: slerp tokenizer_parameters: t: 0.3 # Dà più peso al tokenizer di Gemma-2-Ataraxy-9B base_model: lemon07r/Gemma-2-Ataraxy-9B dtype: bfloat16 parameters: t: [0, 0.3, 0.6, 0.8, 0.6, 0.3, 0] # Curva che favorisce leggermente il centro del merge temp: 2.0 # Temperatura aumentata per un merge più audace density: - threshold: 0.05 t: 0.8 - threshold: 0.3 t: 0.6 - threshold: 0.7 t: 0.4 - threshold: 0.95 t: 0.2 noise: 0.1 # Aggiunto rumore per ulteriore variabilità ``` ## 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/Neithabet-9G-Q8_0-GGUF --hf-file neithabet-9g-q8_0.gguf -p "The meaning to life and the universe is" ``` ### Server: ```bash llama-server --hf-repo Triangle104/Neithabet-9G-Q8_0-GGUF --hf-file neithabet-9g-q8_0.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/Neithabet-9G-Q8_0-GGUF --hf-file neithabet-9g-q8_0.gguf -p "The meaning to life and the universe is" ``` or ``` ./llama-server --hf-repo Triangle104/Neithabet-9G-Q8_0-GGUF --hf-file neithabet-9g-q8_0.gguf -c 2048 ```