Instructions to use hosseinhimself/tara-roberta-base-fa-qa with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hosseinhimself/tara-roberta-base-fa-qa with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("question-answering", model="hosseinhimself/tara-roberta-base-fa-qa")# Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("hosseinhimself/tara-roberta-base-fa-qa") model = AutoModelForQuestionAnswering.from_pretrained("hosseinhimself/tara-roberta-base-fa-qa", device_map="auto") - Notebooks
- Google Colab
- Kaggle
| datasets: | |
| - SajjadAyoubi/persian_qa | |
| language: | |
| - fa | |
| pipeline_tag: question-answering | |
| license: apache-2.0 | |
| library_name: transformers | |
| tags: | |
| - roberta | |
| - question-answering | |
| - Persian | |
| # Tara | |
| <img src="https://huggingface.co/hosseinhimself/tara-roberta-base-fa-qa/resolve/main/OIG1.jpeg" alt="Model Image" width="400" height="400"> | |
| **Tara** 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. | |
| ## Model Description | |
| 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. | |
| ## Usage | |
| To use this model for question-answering tasks, load it with the `transformers` library: | |
| ```python | |
| from transformers import AutoTokenizer, AutoModelForQuestionAnswering, pipeline | |
| model = "hosseinhimself/tara-roberta-base-fa-qa" | |
| # Load the tokenizer and model | |
| tokenizer = AutoTokenizer.from_pretrained(model) | |
| model = AutoModelForQuestionAnswering.from_pretrained(model) | |
| # Create a QA pipeline | |
| qa_pipeline = pipeline("question-answering", model=model, tokenizer=tokenizer) | |
| # Example usage | |
| context = "شرکت فولاد مبارکه در سال 1371 تأسیس شد." | |
| question = "چه زمانی شرکت فولاد مبارکه تأسیس شد؟" | |
| # Modify the pipeline to return answer | |
| results = qa_pipeline(question=question, context=context) | |
| # Display the answer | |
| print(results['answer']) | |
| ``` | |
| ## Datasets | |
| The model was fine-tuned using the [SajjadAyoubi/persian_qa](https://huggingface.co/datasets/SajjadAyoubi/persian_qa) dataset. | |
| ## Languages | |
| The model supports the Persian language. | |
| ## Additional Information | |
| 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). |