---
library_name: transformers
license: apache-2.0
language:
- en
tags:
- llama-cpp
- gguf
- quantized
- smol
- tulu
base_model:
- SultanR/SmolTulu-1.7b-Instruct
pipeline_tag: text-generation
---

# SmolTulu-1.7b-Instruct GGUF!

This is the GGUF version of [SmolTulu-1.7b-Instruct](https://huggingface.co/SultanR/SmolTulu-1.7b-Instruct), quantized to Q4_K_M!

## 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 SultanR/SmolTulu-1.7b-Instruct-GGUF --hf-file smoltulu-1.7b-instruct-q4_k_m.gguf -p "The meaning to life and the universe is"
```

### Server:
```bash
llama-server --hf-repo SultanR/SmolTulu-1.7b-Instruct-GGUF --hf-file smoltulu-1.7b-instruct-q4_k_m.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 SultanR/SmolTulu-1.7b-Instruct-GGUF --hf-file smoltulu-1.7b-instruct-q4_k_m.gguf -p "The meaning to life and the universe is"
```
or 
```
./llama-server --hf-repo SultanR/SmolTulu-1.7b-Instruct-GGUF --hf-file smoltulu-1.7b-instruct-q4_k_m.gguf -c 2048
```