README.md

---
base_model: Iker/Llama-3-Instruct-Neurona-8b-v2
datasets:
- Danielbrdz/Barcenas-Economia
- HiTZ/casimedicos-exp
- somosnlp/coser_resumenes
- csebuetnlp/CrossSum
- Iker/Document-Translation-en-es
- somosnlp/es-inclusive-language-it
- glaiveai/glaive-code-assistant-v3
- glaiveai/glaive-function-calling-v2
- Iker/InstructTranslation-EN-ES
- somosnlp/lenguaje-claro-dataset
- somosnlp/LingComp_QA
- Iker/NoticIA
- teknium/OpenHermes-2.5
- Iker/OpenHermes-2.5-Spanish
- Helsinki-NLP/opus-100
- projecte-aina/RAG_Multilingual
- HiTZ/This-is-not-a-dataset
- Iker/Reddit-Post-Translation
- wikipedia
language:
- es
- en
library_name: transformers
license: llama3
pipeline_tag: text-generation
tags:
- synthetic
- llama-cpp
- gguf-my-repo
---

# NikolayKozloff/Llama-3-Instruct-Neurona-8b-v2-Q4_0-GGUF
This model was converted to GGUF format from [`Iker/Llama-3-Instruct-Neurona-8b-v2`](https://huggingface.co/Iker/Llama-3-Instruct-Neurona-8b-v2) 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/Iker/Llama-3-Instruct-Neurona-8b-v2) for more details on the model.

## 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 NikolayKozloff/Llama-3-Instruct-Neurona-8b-v2-Q4_0-GGUF --hf-file llama-3-instruct-neurona-8b-v2-q4_0.gguf -p "The meaning to life and the universe is"
```

### Server:
```bash
llama-server --hf-repo NikolayKozloff/Llama-3-Instruct-Neurona-8b-v2-Q4_0-GGUF --hf-file llama-3-instruct-neurona-8b-v2-q4_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 NikolayKozloff/Llama-3-Instruct-Neurona-8b-v2-Q4_0-GGUF --hf-file llama-3-instruct-neurona-8b-v2-q4_0.gguf -p "The meaning to life and the universe is"
```
or 
```
./llama-server --hf-repo NikolayKozloff/Llama-3-Instruct-Neurona-8b-v2-Q4_0-GGUF --hf-file llama-3-instruct-neurona-8b-v2-q4_0.gguf -c 2048
```