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--- |
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base_model: nbeerbower/Mahou-1.5-mistral-nemo-12B-lorablated |
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library_name: transformers |
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tags: |
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- mergekit |
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- merge |
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- llama-cpp |
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- gguf-my-repo |
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--- |
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# Triangle104/Mahou-1.5-mistral-nemo-12B-lorablated-Q4_K_S-GGUF |
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This model was converted to GGUF format from [`nbeerbower/Mahou-1.5-mistral-nemo-12B-lorablated`](https://huggingface.co/nbeerbower/Mahou-1.5-mistral-nemo-12B-lorablated) using llama.cpp via the ggml.ai's [GGUF-my-repo](https://huggingface.co/spaces/ggml-org/gguf-my-repo) space. |
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Refer to the [original model card](https://huggingface.co/nbeerbower/Mahou-1.5-mistral-nemo-12B-lorablated) for more details on the model. |
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--- |
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Model details: |
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- |
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This is a merge of pre-trained language models created using mergekit. |
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Merge Details |
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Merge Method |
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This model was merged using the task arithmetic merge method using flammenai/Mahou-1.5-mistral-nemo-12B + nbeerbower/Mistral-Nemo-12B-abliterated-LORA as a base. |
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Models Merged |
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The following models were included in the merge: |
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Configuration |
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The following YAML configuration was used to produce this model: |
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base_model: flammenai/Mahou-1.5-mistral-nemo-12B+nbeerbower/Mistral-Nemo-12B-abliterated-LORA |
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dtype: bfloat16 |
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merge_method: task_arithmetic |
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parameters: |
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normalize: false |
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slices: |
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- sources: |
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- layer_range: [0, 32] |
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model: flammenai/Mahou-1.5-mistral-nemo-12B+nbeerbower/Mistral-Nemo-12B-abliterated-LORA |
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parameters: |
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weight: 1.0 |
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--- |
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## Use with llama.cpp |
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Install llama.cpp through brew (works on Mac and Linux) |
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```bash |
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brew install llama.cpp |
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``` |
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Invoke the llama.cpp server or the CLI. |
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### CLI: |
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```bash |
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llama-cli --hf-repo Triangle104/Mahou-1.5-mistral-nemo-12B-lorablated-Q4_K_S-GGUF --hf-file mahou-1.5-mistral-nemo-12b-lorablated-q4_k_s.gguf -p "The meaning to life and the universe is" |
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``` |
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### Server: |
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```bash |
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llama-server --hf-repo Triangle104/Mahou-1.5-mistral-nemo-12B-lorablated-Q4_K_S-GGUF --hf-file mahou-1.5-mistral-nemo-12b-lorablated-q4_k_s.gguf -c 2048 |
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``` |
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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. |
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Step 1: Clone llama.cpp from GitHub. |
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``` |
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git clone https://github.com/ggerganov/llama.cpp |
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``` |
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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). |
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``` |
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cd llama.cpp && LLAMA_CURL=1 make |
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``` |
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Step 3: Run inference through the main binary. |
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``` |
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./llama-cli --hf-repo Triangle104/Mahou-1.5-mistral-nemo-12B-lorablated-Q4_K_S-GGUF --hf-file mahou-1.5-mistral-nemo-12b-lorablated-q4_k_s.gguf -p "The meaning to life and the universe is" |
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``` |
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or |
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``` |
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./llama-server --hf-repo Triangle104/Mahou-1.5-mistral-nemo-12B-lorablated-Q4_K_S-GGUF --hf-file mahou-1.5-mistral-nemo-12b-lorablated-q4_k_s.gguf -c 2048 |
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``` |
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