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--- |
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base_model: ToastyPigeon/Gemma-3-Starshine-12B |
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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/Gemma-3-Starshine-12B-Q4_K_S-GGUF |
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This model was converted to GGUF format from [`ToastyPigeon/Gemma-3-Starshine-12B`](https://huggingface.co/ToastyPigeon/Gemma-3-Starshine-12B) 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/ToastyPigeon/Gemma-3-Starshine-12B) for more details on the model. |
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--- |
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A creative writing model based on a merge of fine-tunes on Gemma 3 12B IT and Gemma 3 12B PT. |
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This is the Story Focused merge. This version works |
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better for storytelling and scenarios, as the prose is more novel-like |
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and it has a tendency to impersonate the user character. |
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See the Alternate RP Focused version as well. |
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This is a merge of two G3 models, one trained on instruct and one trained on base: |
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- allura-org/Gemma-3-Glitter-12B - Itself a merge of a storywriting and RP train (both also by ToastyPigeon), on instruct |
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- ToastyPigeon/Gemma-3-Confetti-12B - Experimental application of the Glitter data using base instead of |
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instruct, additionally includes some adventure data in the form of |
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SpringDragon. |
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The result is a lovely blend of Glitter's ability to follow |
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instructions and Confetti's free-spirit prose, effectively 'loosening |
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up' much of the hesitancy that was left in Glitter. |
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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/Gemma-3-Starshine-12B-Q4_K_S-GGUF --hf-file gemma-3-starshine-12b-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/Gemma-3-Starshine-12B-Q4_K_S-GGUF --hf-file gemma-3-starshine-12b-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/Gemma-3-Starshine-12B-Q4_K_S-GGUF --hf-file gemma-3-starshine-12b-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/Gemma-3-Starshine-12B-Q4_K_S-GGUF --hf-file gemma-3-starshine-12b-q4_k_s.gguf -c 2048 |
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``` |
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