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  ## Introduction
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  ## How to run (transformers)
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  ### Install transformers
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  gen_text = tokenizer.decode(gen_tokens[0])
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  print(gen_text)
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- ```
 
 
 
 
 
 
 
 
 
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  ## Introduction
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+ 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.
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+ 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.
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+ 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.
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+ ### The name
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+ <p align="center">
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+ <img src="https://github.com/Mann-E/hormoz/blob/main/hormoz-logo.png?raw=true" width=768px />
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+ </p>
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+ 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.
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  ## How to run (transformers)
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  ### Install transformers
 
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  gen_text = tokenizer.decode(gen_tokens[0])
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  print(gen_text)
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+ ```
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+ ## License
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+ This model is published under _MIT_ license.
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+ ### Commercial Use
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+ 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.