---
license: mit
base_model: open-neo/Kyro-n1-3B
library_name: transformers
language:
- en
- zh
- fr
- es
- pt
- de
- it
- ru
- ja
- ko
- vi
- th
- ar
- fa
- he
- tr
- cs
- pl
- hi
- bn
- ur
- id
- ms
- lo
- my
- ceb
- km
- tl
- nl
tags:
- trl
- Reasoning
- open-llm
- synthetic-data
- Deepseek-R1
- Qwen2.5
- fine-tune
- unsloth
- Conversational
- Agentic
- llama-cpp
- gguf-my-repo
---

# Spestly/Kyro-n1-3B-Q6_K-GGUF
This model was converted to GGUF format from [`open-neo/Kyro-n1-3B`](https://huggingface.co/open-neo/Kyro-n1-3B) 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/open-neo/Kyro-n1-3B) 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 Spestly/Kyro-n1-3B-Q6_K-GGUF --hf-file kyro-n1-3b-q6_k.gguf -p "The meaning to life and the universe is"
```

### Server:
```bash
llama-server --hf-repo Spestly/Kyro-n1-3B-Q6_K-GGUF --hf-file kyro-n1-3b-q6_k.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 Spestly/Kyro-n1-3B-Q6_K-GGUF --hf-file kyro-n1-3b-q6_k.gguf -p "The meaning to life and the universe is"
```
or 
```
./llama-server --hf-repo Spestly/Kyro-n1-3B-Q6_K-GGUF --hf-file kyro-n1-3b-q6_k.gguf -c 2048
```