| --- |
| license: mit |
| language: |
| - en |
| - fr |
| - de |
| - es |
| - it |
| - pt |
| - ja |
| - ko |
| - zh |
| - ar |
| - el |
| - fa |
| - pl |
| - id |
| - cs |
| - he |
| - hi |
| - nl |
| - ro |
| - ru |
| - tr |
| - uk |
| - vi |
| datasets: |
| - xmanii/mauxi-talk-pro |
| - xmanii/mauxitalk-persian |
| --- |
| |
| # Hormoz 8B |
|
|
| ## Introduction |
|
|
| This model is an effort in order to make a multi-lingual and _on device_ models which can be executed on the consumer hardware. The model follows the steps used in training _DeepSeek_ model. However, the model is _not a reasoning model_ and a generic question answering, conversational and _uncensored_ model which has been made with a cost of around $4000 USD. |
|
|
| If you're curious about the model you also can see our [GitHub](https://github.com/mann-e/hormoz) and learn more about the benchmarks and costs. |
|
|
| Also, this model is based on _Command R_'s architecture, since that architecture gave us the best results in multilingual chat. Specially with languages such as _Persian_ and _Arabic_. This way, you can consider this model like a commercially useaeble version of _aya expanse_ as well. |
|
|
| ### The name |
|
|
| <p align="center"> |
| <img src="https://github.com/Mann-E/hormoz/blob/main/hormoz-logo.png?raw=true" width=768px /> |
| </p> |
|
|
| The name __Hormoz__ comes from the Persian word "هرمز" which has multiple meanings. It can point to the _strait of Hormoz_ in Persian Gulf or _Hormoz Island_ which is part of the Hormozgan Province in the south of Iran. Also it may point to "اورمزد" or _Ourmozd_ which is middle/ancient Persian name for the planet _Jupiter_ and derived from the term _Ahura Mazda_ or the Avestan term for God. |
|
|
| ## How to run (transformers) |
|
|
| ### Free API |
|
|
| The model is also available through [Jabir Project's API](https://jabirproject.org/api-docs) and [Pollinations.AI](https://pollinations.ai). |
|
|
| ### Install transformers |
|
|
| ``` |
| pip install transformers --upgrade |
| ``` |
|
|
| _Note:_ For better performance, you may need to install `accelerate` package as well. |
|
|
| ### Inference |
|
|
| ```python |
| from transformers import AutoTokenizer, AutoModelForCausalLM |
| |
| model_id = "mann-e/Hormoz-8B" |
| tokenizer = AutoTokenizer.from_pretrained(model_id) |
| model = AutoModelForCausalLM.from_pretrained(model_id).to("cuda") |
| |
| messages = [{"role": "user", "content": "What is the answer to universe, life and everything?"}] |
| input_ids = tokenizer.apply_chat_template(messages, tokenize=True, add_generation_prompt=True, return_tensors="pt").to("cuda") |
| |
| gen_tokens = model.generate( |
| input_ids, |
| max_new_tokens=1024, |
| do_sample=True, |
| temperature=1.0, |
| ) |
| |
| gen_text = tokenizer.decode(gen_tokens[0]) |
| print(gen_text) |
| ``` |
|
|
| ## License |
|
|
| This model is published under _MIT_ license. |
|
|
| ### Commercial Use |
|
|
| Since this model is MIT licensed, you're free to do whatever you want with the model. However since we're a relatively small startup, we recommend you if you are a big corporate and you host this model, give us a capacity of your API as well. This way, we both can benefit from the model. |
