---
license: other
tags:
- llama-cpp
- gguf-my-repo
base_model: AGI-0/Art-v0-3B
---

# Triangle104/Art-v0-3B-Q5_K_S-GGUF
This model was converted to GGUF format from [`AGI-0/Art-v0-3B`](https://huggingface.co/AGI-0/Art-v0-3B) 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/AGI-0/Art-v0-3B) for more details on the model.

---
Model details:
-
Auto Regressive Thinker (Art) v0 3B

Art v0 3B is our inaugural model in the Art series, fine-tuned from Qwen/Qwen2.5-3B-Instruct using a specialized dataset generated with Gemini 2.0 Flash Thinking. Read more about the Art series
Model Details

    Base Model: Qwen2.5-3B-Instruct
    Architecture: Transformer
    Size: 3B parameters

Usage

The model incorporates a reasoning mechanism using specific tags:

<|start_reasoning|> model's reasoning process <|end_reasoning|> model's response

Recommendations

    Use the model without quantization
    Use the tokenizer chat template
    Use a low temperature 0.1-0.3 and repetition_penalty of 1.1

Training Details

This experimental model was trained on a curated dataset generated using Gemini 2.0 Flash Thinking. Detailed training methodology, dataset, and code are available exclusively to our community members.
About Us

We are a community-funded AI research lab focused on advancing open-source AGI development. Our community members support us through Patreon donations.
Community Access

Our supporters get exclusive access to:

    Training dataset
    Training code and methodology
    Behind-the-scenes development insights
    Future model previews

---
## 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/Art-v0-3B-Q5_K_S-GGUF --hf-file art-v0-3b-q5_k_s.gguf -p "The meaning to life and the universe is"
```

### Server:
```bash
llama-server --hf-repo Triangle104/Art-v0-3B-Q5_K_S-GGUF --hf-file art-v0-3b-q5_k_s.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/Art-v0-3B-Q5_K_S-GGUF --hf-file art-v0-3b-q5_k_s.gguf -p "The meaning to life and the universe is"
```
or 
```
./llama-server --hf-repo Triangle104/Art-v0-3B-Q5_K_S-GGUF --hf-file art-v0-3b-q5_k_s.gguf -c 2048
```