---
base_model: AtlaAI/Selene-1-Mini-Llama-3.1-8B
library_name: transformers
language:
- en
- de
- fr
- it
- pt
- es
pipeline_tag: text-generation
tags:
- llama
- atla
- evaluation
- llm-as-a-judge
- meta
- conversational
- lm-judge
- llama-cpp
- gguf-my-repo
license: llama3.1
---


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<p align="center">
    🛝 <a href="https://hf.co/spaces/AtlaAI/selene">Playground</a> | 
    📄 <a href="https://huggingface.co/spaces/AtlaAI/selene-1-mini-tech-report">Technical report</a> | 
    💻 <a href="https://github.com/atla-ai/selene-mini">GitHub</a> | 
    👀 <a href="https://www.atla-ai.com/sign-up-waitlist?utm_source=huggingface&utm_medium=community&utm_campaign=WL_HF_all_communitypost_sel1minilaunch" style="background-image: linear-gradient(to right, red, orange, yellow, green, blue, indigo, violet); -webkit-background-clip: text; color: transparent; animation: rainbow 5s ease infinite; text-decoration: underline; text-decoration-color: currentColor;">Sign up for the API</a>
</p>

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# AtlaAI/Selene-1-Mini-Llama-3.1-8B-Q8_0-GGUF
This model was converted to GGUF format from [`AtlaAI/Selene-1-Mini-Llama-3.1-8B`](https://huggingface.co/AtlaAI/Selene-1-Mini-Llama-3.1-8B) 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/AtlaAI/Selene-1-Mini-Llama-3.1-8B) 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 spisupat/Selene-1-Mini-Llama-3.1-8B-Q8_0-GGUF --hf-file selene-1-mini-llama-3.1-8b-q8_0.gguf -p "The meaning to life and the universe is"
```

### Server:
```bash
llama-server --hf-repo spisupat/Selene-1-Mini-Llama-3.1-8B-Q8_0-GGUF --hf-file selene-1-mini-llama-3.1-8b-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 spisupat/Selene-1-Mini-Llama-3.1-8B-Q8_0-GGUF --hf-file selene-1-mini-llama-3.1-8b-q8_0.gguf -p "The meaning to life and the universe is"
```
or 
```
./llama-server --hf-repo spisupat/Selene-1-Mini-Llama-3.1-8B-Q8_0-GGUF --hf-file selene-1-mini-llama-3.1-8b-q8_0.gguf -c 2048
```