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README.md
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---
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base_model:
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- sam-paech/Darkest-muse-v1
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- TheDrummer/Tiger-Gemma-9B-v3
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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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---
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# Darkest-Tiger-Gemma-v1-
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This is a **creative, uncensored** merge of pre-trained language models created using [mergekit](https://github.com/cg123/mergekit).
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---
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This model was converted to GGUF format from [`Fentible/Darkest-Tiger-Gemma-v1
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**GGUF Repo Suite** is based on a refactored fork of ggml.ai's [GGUF-my-repo](https://huggingface.co/spaces/ggml-org/gguf-my-repo) space, updated for offline use with windows and support for lower IQ quants.
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**imatrix.dat** generated using bartowski's [calibration_datav3.txt](https://gist.github.com/bartowski1182/eb213dccb3571f863da82e99418f81e8)
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Refer to the [original model card](https://huggingface.co/Fentible/Darkest-Tiger-Gemma-v1
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---
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## Merge Details
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### Merge Method
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This model was merged using the [SLERP](https://en.wikipedia.org/wiki/Slerp) merge method.
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### Models Merged
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The following models were included in the merge:
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* [sam-paech/Darkest-muse-v1](https://huggingface.co/sam-paech/Darkest-muse-v1)
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* [TheDrummer/Tiger-Gemma-9B-v3](https://huggingface.co/TheDrummer/Tiger-Gemma-9B-v3)
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### Configuration
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The following YAML configuration was used to produce this model:
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```yaml
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base_model: TheDrummer/Tiger-Gemma-9B-v3
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merge_method: slerp
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dtype: bfloat16
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slices:
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- sources:
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- model: sam-paech/Darkest-muse-v1
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layer_range: [0, 42]
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- model: TheDrummer/Tiger-Gemma-9B-v3
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layer_range: [0, 42]
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parameters:
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t: 0.5
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```
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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 Fentible/
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```
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### Server:
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```bash
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llama-server --hf-repo Fentible/
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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 Fentible/
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```
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or
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```
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./llama-server --hf-repo Fentible/
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```
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---
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base_model:
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- sam-paech/Darkest-muse-v1
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- TheDrummer/Tiger-Gemma-9B-v3
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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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---
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# Darkest-Tiger-Gemma-9B-v1-GGUF
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This is a **creative, uncensored** merge of pre-trained language models created using [mergekit](https://github.com/cg123/mergekit).
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+

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+
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---
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This model was converted to GGUF format from [`Fentible/Darkest-Tiger-Gemma-9B-v1`](https://huggingface.co/Fentible/Darkest-Tiger-Gemma-9B-v1) using llama.cpp via the Fentible's [GGUF-repo-suite](https://huggingface.co/spaces/fentible/gguf-repo-suite).
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**GGUF Repo Suite** is based on a refactored fork of ggml.ai's [GGUF-my-repo](https://huggingface.co/spaces/ggml-org/gguf-my-repo) space, updated for offline use with windows and support for lower IQ quants.
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**imatrix.dat** generated using bartowski's [calibration_datav3.txt](https://gist.github.com/bartowski1182/eb213dccb3571f863da82e99418f81e8)
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+
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Refer to the [original model card](https://huggingface.co/Fentible/Darkest-Tiger-Gemma-9B-v1) for more details on the model.
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---
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## Merge Details
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### Merge Method
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This model was merged using the [SLERP](https://en.wikipedia.org/wiki/Slerp) merge method.
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### Models Merged
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The following models were included in the merge:
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* [sam-paech/Darkest-muse-v1](https://huggingface.co/sam-paech/Darkest-muse-v1)
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* [TheDrummer/Tiger-Gemma-9B-v3](https://huggingface.co/TheDrummer/Tiger-Gemma-9B-v3)
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### Configuration
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The following YAML configuration was used to produce this model:
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```yaml
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base_model: TheDrummer/Tiger-Gemma-9B-v3
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merge_method: slerp
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dtype: bfloat16
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slices:
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- sources:
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- model: sam-paech/Darkest-muse-v1
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layer_range: [0, 42]
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- model: TheDrummer/Tiger-Gemma-9B-v3
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layer_range: [0, 42]
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parameters:
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t: 0.5
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```
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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 Fentible/Darkest-Tiger-Gemma-9B-v1 --hf-file Darkest-Tiger-Gemma-9B-v1-IQ4_XS.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 Fentible/Darkest-Tiger-Gemma-9B-v1 --hf-file Darkest-Tiger-Gemma-9B-v1-IQ4_XS.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 Fentible/Darkest-Tiger-Gemma-9B-v1 --hf-file Darkest-Tiger-Gemma-9B-v1-IQ4_XS.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 Fentible/Darkest-Tiger-Gemma-9B-v1 --hf-file Darkest-Tiger-Gemma-9B-v1-IQ4_XS.gguf -c 2048
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```
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