---
base_model: Spestly/Athena-3-7B
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
library_name: transformers
license: mit
tags:
- chemistry
- biology
- code
- text-generation-inference
- STEM
- unsloth
- llama-cpp
- gguf-my-repo
---

# Triangle104/Athena-3-7B-Q4_K_S-GGUF
This model was converted to GGUF format from [`Spestly/Athena-3-7B`](https://huggingface.co/Spestly/Athena-3-7B) 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/Spestly/Athena-3-7B) for more details on the model.

---
Athena-3-7B is a 7.68-billion-parameter causal language
 model fine-tuned from Qwen2.5-Math-7B. This model is designed to excel 
in STEM reasoning, mathematics, and natural language processing tasks, 
offering advanced instruction-following and problem-solving 
capabilities.

Training Details
-
Athena-3-7B was fine-tuned using the Unsloth framework on a single 
NVIDIA A100 GPU. The fine-tuning process spanned approximately 90 
minutes over 60 epochs, utilizing a curated dataset focused on 
instruction-following, problem-solving, and advanced mathematics. This 
approach enhances the model's capabilities in academic and analytical 
tasks.

Intended Use
-
Athena-3-7B is designed for a range of applications, including but not limited to:

-STEM Reasoning: Assisting with complex problem-solving and theoretical explanations.

-Academic Assistance: Supporting tutoring, step-by-step math solutions, and scientific writing.

-General NLP Tasks: Text generation, summarization, and question answering.

-Data Analysis: Interpreting and explaining mathematical and statistical data.


While Athena-3-7B is a powerful tool for various applications, it is 
not intended for real-time, safety-critical systems or for processing 
sensitive personal information.

Limitations
-
Users should be aware of the following limitations:

-Biases: Athena-3-7B may exhibit biases present in 
its training data. Users should critically assess outputs, especially in
 sensitive contexts.

-Knowledge Cutoff: The model's knowledge is current up to August 2024. It may not be aware of events or developments occurring after this date.

-Language Support: While the model supports multiple languages, performance is strongest in English and technical content.

Acknowledgements
-
Athena-3-7B builds upon the work of the Qwen team. Gratitude is also 
extended to the open-source AI community for their contributions to 
tools and frameworks that facilitated the development of Athena-3-7B.

License
-
Athena-3-7B is released under the MIT License, permitting wide usage with proper attribution.

---
## 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/Athena-3-7B-Q4_K_S-GGUF --hf-file athena-3-7b-q4_k_s.gguf -p "The meaning to life and the universe is"
```

### Server:
```bash
llama-server --hf-repo Triangle104/Athena-3-7B-Q4_K_S-GGUF --hf-file athena-3-7b-q4_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/Athena-3-7B-Q4_K_S-GGUF --hf-file athena-3-7b-q4_k_s.gguf -p "The meaning to life and the universe is"
```
or 
```
./llama-server --hf-repo Triangle104/Athena-3-7B-Q4_K_S-GGUF --hf-file athena-3-7b-q4_k_s.gguf -c 2048
```