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---
base_model: ToastyPigeon/Gemma-3-Starshine-12B
library_name: transformers
tags:
- mergekit
- merge
- llama-cpp
- gguf-my-repo
---
# Triangle104/Gemma-3-Starshine-12B-Q4_K_M-GGUF
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.
Refer to the [original model card](https://huggingface.co/ToastyPigeon/Gemma-3-Starshine-12B) for more details on the model.
---
A creative writing model based on a merge of fine-tunes on Gemma 3 12B IT and Gemma 3 12B PT.
This is the Story Focused merge. This version works
better for storytelling and scenarios, as the prose is more novel-like
and it has a tendency to impersonate the user character.
See the Alternate RP Focused version as well.
This is a merge of two G3 models, one trained on instruct and one trained on base:
- allura-org/Gemma-3-Glitter-12B - Itself a merge of a storywriting and RP train (both also by ToastyPigeon), on instruct
- ToastyPigeon/Gemma-3-Confetti-12B - Experimental application of the Glitter data using base instead of
instruct, additionally includes some adventure data in the form of
SpringDragon.
The result is a lovely blend of Glitter's ability to follow
instructions and Confetti's free-spirit prose, effectively 'loosening
up' much of the hesitancy that was left in Glitter.
---
## 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/Gemma-3-Starshine-12B-Q4_K_M-GGUF --hf-file gemma-3-starshine-12b-q4_k_m.gguf -p "The meaning to life and the universe is"
```
### Server:
```bash
llama-server --hf-repo Triangle104/Gemma-3-Starshine-12B-Q4_K_M-GGUF --hf-file gemma-3-starshine-12b-q4_k_m.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/Gemma-3-Starshine-12B-Q4_K_M-GGUF --hf-file gemma-3-starshine-12b-q4_k_m.gguf -p "The meaning to life and the universe is"
```
or
```
./llama-server --hf-repo Triangle104/Gemma-3-Starshine-12B-Q4_K_M-GGUF --hf-file gemma-3-starshine-12b-q4_k_m.gguf -c 2048
```
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