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  # Paya (aya 23 8B Instruction Tuned on Farsi)
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- <a href="https://ibb.co/fHmCngh"><img src="https://i.ibb.co/jD7LWNc/paya.png" alt="paya" border="0"></a>
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  # Paya (aya 23 8B Instruction Tuned on Farsi)
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+ <a href="https://ibb.co/fHmCngh"><img src="https://i.ibb.co/jD7LWNc/paya.png" alt="paya" border="0"></a>
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+ Welcome to PAYA, a powerful Persian text generation model built upon the foundations of Aya 23 8B, a multilingual language model. PAYA has been fine-tuned using the supervised finetuning technique, employing the DORA method for efficient refinement on Persian datasets, particularly leveraging the [persian-alpaca-deep-clean](https://huggingface.co/datasets/myrkur/persian-alpaca-deep-clean) dataset.
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+
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+ ## Features
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+ - **Advanced Text Generation**: Generate coherent and contextually relevant Persian text with ease.
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+ - **Efficient Fine-Tuning**: Utilizes the DORA method for streamlined fine-tuning on Persian datasets.
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+ - **Optimized Tokenization**: The model's tokenizer ensures accurate representation of Persian words, enhancing the quality of generated text.
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+
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+ ## Usage
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+ You can quickly get started with PAYA using the following sample code:
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+ ```python
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+ import transformers
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+ import torch
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+
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+ model_id = "myrkur/paya"
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+
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+ pipeline = transformers.pipeline(
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+ "text-generation",
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+ model=model_id,
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+ model_kwargs={"torch_dtype": torch.bfloat16},
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+ device_map="auto",
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+ )
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+
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+ messages = [
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+ {"role": "user", "content": "علم بهتر است یا ثروت؟"},
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+ ]
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+
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+ prompt = pipeline.tokenizer.apply_chat_template(
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+ messages,
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+ tokenize=False,
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+ add_generation_prompt=True
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+ )
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+
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+ terminators = [
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+ pipeline.tokenizer.eos_token_id,
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+ ]
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+
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+ outputs = pipeline(
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+ prompt,
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+ max_new_tokens=512,
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+ eos_token_id=terminators,
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+ do_sample=True,
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+ temperature=0.4,
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+ top_p=0.9,
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+ repetition_penalty=1.1
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+ )
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+ print(outputs[0]["generated_text"][len(prompt):])
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+ ```
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+
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+ ## Why PAYA?
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+
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+ PAYA stands out for its exceptional tokenization capabilities, accurately capturing the nuances of the Persian language. Additionally, its fine-tuned parameters and efficient training methodology ensure remarkable results in text generation tasks.
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+
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+ ## Contributions
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+ Contributions to PAYA are welcome! Whether it's enhancing the model's capabilities, improving its performance on specific tasks, or evaluating its performance, your contributions can help advance Persian natural language processing.
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+
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+ ## Contact
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+ For questions or further information, please contact:
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+ - Amir Masoud Ahmadi: [amirmasoud.ahkol@gmail.com](mailto:amirmasoud.ahkol@gmail.com)