Zion_Alpha

<div align="center"> <b style="font-size: 40px;">Zion_Alpha</b> </div> <img src="https://i.imgur.com/e1LEQ18.png" alt="Zion_Alpha" style="width: 50%; min-width: 400px; display: block; margin: auto;">

Model Details

Zion_Alpha is the first REAL Hebrew model in the world. It wasn't finetuned for any tasks yet, but it actually understands and comprehends Hebrew. It can even do some decent translation. I've tested GPT4 vs Zion_Alpha, and out of the box, Zion_Alpha did a better job translating. I did the finetune using SOTA techniques and using my insights from years of underwater basket weaving. If you wanna offer me a job, just add me on Facebook.

Future Plans

I plan to perform a SLERP merge with one of my other fine-tuned models, which has a bit more knowledge about Israeli topics. Additionally, I might create a larger model using MergeKit, but we'll see how it goes.

Looking for Sponsors

Since all my work is done on-premises, I am constrained by my current hardware. I would greatly appreciate any support in acquiring an A6000, which would enable me to train significantly larger models much faster.

Papers?

Maybe. We'll see. No promises here 🤓

Contact Details

I'm not great at self-marketing (to say the least) and don't have any social media accounts. If you'd like to reach out to me, you can email me at [email protected]. Please note that this email might receive more messages than I can handle, so I apologize in advance if I can't respond to everyone.

Versions and QUANTS

• Base model: FP16
• Instruction tuned: FP16 | GGUF

Model architecture

Based on Mistral 7B. I didn't even bother to alter the tokenizer.

The recommended prompt setting is Debug-deterministic:

temperature: 1
top_p: 1
top_k: 1
typical_p: 1
min_p: 1
repetition_penalty: 1

The recommended instruction template is Mistral:

{%- for message in messages %}
    {%- if message['role'] == 'system' -%}
        {{- message['content'] -}}
    {%- else -%}
        {%- if message['role'] == 'user' -%}
            {{-'[INST] ' + message['content'].rstrip() + ' [/INST]'-}}
        {%- else -%}
            {{-'' + message['content'] + '</s>' -}}
        {%- endif -%}
    {%- endif -%}
{%- endfor -%}
{%- if add_generation_prompt -%}
    {{-''-}}
{%- endif -%}

English to hebrew example:

<div align="center"> <b style="font-size: 40px;">Zion_Alpha English to Hebrew example</b> </div> <img src="https://i.imgur.com/JnTuawF.png" alt="Zion_Alpha" style="width: 40%; min-width: 600px; display: block; margin: auto;">

English to hebrew example:

<div align="center"> <b style="font-size: 40px;">Zion_Alpha Hebrew to English example</b> </div> <img src="https://i.imgur.com/Wm2igLJ.png" alt="Zion_Alpha" style="width: 40%; min-width: 600px; display: block; margin: auto;"> <div align="center"> <b style="font-size: 30px;">Unscripted video: live zero shot demonstration at story writing capabilities in Hebrew</b>

</div> <div align="center"> <b style="font-size: 30px;">Zion_Alpha VS Mistral 'Hebrew' Live & unscripted in real time</b>

</div> <div align="center"> <b style="font-size: 30px;">Zion_Alpha VS Mistral 'Hebrew' Live & unscripted in real time Long text translation</b>

</div>

History

The model was originally trained about 2 month after Mistral (v0.1) was released. As of 04 June 2024, Zion_Alpha got the Highest SNLI score in the world among open source models in Hebrew, surpassing most of the models by a huge margin. (84.05 score)

<img src="https://huggingface.co/SicariusSicariiStuff/Zion_Alpha/resolve/main/Images/Zion_Alpha.png" alt="Zion_Alpha SNLI Score" style="width: 100%; min-width: 700px; display: block; margin: auto;">

---

Citation Information

@llm{Zion_Alpha,
  author = {SicariusSicariiStuff},
  title = {Zion_Alpha},
  year = {2024},
  publisher = {Hugging Face},
  url = {https://huggingface.co/SicariusSicariiStuff/Zion_Alpha}
}

---

Benchmarks

Support

<img src="https://i.imgur.com/0lHHN95.png" alt="GPUs too expensive" style="width: 10%; min-width: 100px; display: block; margin: left;">

• My Ko-fi page ALL donations will go for research resources and compute, every bit counts 🙏🏻
• My Patreon ALL donations will go for research resources and compute, every bit counts 🙏🏻