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--- |
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license: mit |
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datasets: |
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- HariprasathSB/tamil_summarization |
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language: |
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- en |
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- ta |
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tags: |
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- summarization |
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- translation |
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--- |
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# Tamil Summarization and English-to-Tamil Translation Model |
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## Overview |
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This repository contains a fine-tuned model for both Tamil summarization and English-to-Tamil translation. The model was fine-tuned using the Hugging Face Transformers library. This README provides information on how to use the model and its capabilities. |
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## Model Details |
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- **Model Name**: [suriya7/Tamil-Summarization] |
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- **Model Type**: [Summarization , Translation] |
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- **Framework**: Hugging Face Transformers |
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- **Original Model**: [Mr-Vicky-01/Fine_tune_english_to_tamil](Mr-Vicky-01/Fine_tune_english_to_tamil) |
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- **Fine-tuning Dataset**: [HariprasathSB/tamil_summarization](https://huggingface.co/datasets/HariprasathSB/tamil_summarization) |
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- **Languages Supported**: English, Tamil |
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## Model Performance |
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## Usage |
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### Installation |
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You can install the necessary dependencies using pip: |
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```bash |
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pip install transformers |
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``` |
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## Inference |
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Below is an example of how to use the model for both summarization and translation tasks: |
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```python |
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# Load model directly |
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from transformers import AutoTokenizer, AutoModelForSeq2SeqLM |
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tokenizer = AutoTokenizer.from_pretrained("suriya7/Tamil-Summarization") |
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model = AutoModelForSeq2SeqLM.from_pretrained("suriya7/Tamil-Summarization") |
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- **Example English-to-Tamil Translation** |
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input_text = "This is an example English sentence." |
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input_ids = tokenizer.encode(input_text, return_tensors="pt").input_ids |
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outputs = model.generate(input_ids,max_length=128) |
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translated_text = tokenizer.decode(outputs[0], skip_special_tokens=True) |
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print("Translated Tamil Sentence:", translated_text) |
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- **Example Tamil Summarization** |
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tamil_article = "தமிழ் உரையினை சுருக்கமாக சுருக்கமாக உரையிடுவது எப்படி?" |
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tamil_input_ids = tokenizer.encode(tamil_article, return_tensors="pt",truncation=True).input_ids |
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summary_ids = model.generate(tamil_input_ids, max_length=128) |
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summary = tokenizer.decode(summary_ids[0], skip_special_tokens=True) |
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print("Summarized Tamil Text:", summary) |
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``` |
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## Model Output |
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- **For translation tasks, the model outputs translated text in Tamil.** |
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- **For summarization tasks, the model outputs a summarized version of the input Tamil text.** |
