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--- |
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datasets: |
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- SajjadAyoubi/persian_qa |
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language: |
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- fa |
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pipeline_tag: question-answering |
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license: apache-2.0 |
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library_name: transformers |
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tags: |
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- roberta |
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- question-answering |
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- Persian |
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--- |
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# Tara-Roberta-Base-FA-QA |
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**Tara-Roberta-Base-FA-QA** is a fine-tuned version of the `facebookAI/roberta-base` model for question-answering tasks, trained on the [SajjadAyoubi/persian_qa](https://huggingface.co/datasets/SajjadAyoubi/persian_qa) dataset. This model is designed to understand and generate answers to questions posed in Persian. |
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## Model Description |
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This model was fine-tuned on a dataset containing Persian question-answering pairs. It leverages the `roberta-base` architecture to provide answers based on the context provided. The training process was performed with a focus on improving the model's ability to handle Persian text and answer questions effectively. |
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## Usage |
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To use this model for question-answering tasks, load it with the `transformers` library: |
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```python |
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from transformers import AutoTokenizer, AutoModelForQuestionAnswering, pipeline |
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model = "hosseinhimself/tara-roberta-base-fa-qa" |
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# Load the tokenizer and model |
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tokenizer = AutoTokenizer.from_pretrained(model) |
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model = AutoModelForQuestionAnswering.from_pretrained(model) |
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# Create a QA pipeline |
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qa_pipeline = pipeline("question-answering", model=model, tokenizer=tokenizer) |
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# Example usage |
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context = "شرکت فولاد مبارکه در سال 1371 تأسیس شد." |
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question = "چه زمانی شرکت فولاد مبارکه تأسیس شد؟" |
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# Modify the pipeline to return answer |
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results = qa_pipeline(question=question, context=context) |
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# Display the answer |
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print(results['answer']) |
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``` |
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## Datasets |
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The model was fine-tuned using the [SajjadAyoubi/persian_qa](https://huggingface.co/datasets/SajjadAyoubi/persian_qa) dataset. |
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## Languages |
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The model supports the Persian language. |
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## Additional Information |
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For more details on how to fine-tune similar models or to report issues, please visit the [Hugging Face documentation](https://huggingface.co/docs/transformers). |