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---
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
```
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