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--- |
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license: mit |
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datasets: Hemanth-thunder/en_ta |
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language: |
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- ta |
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- en |
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widget: |
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- text: Actor Vijay is competing an 2026 election. |
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- text: you have to study well for exams |
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- text: The Sun is approximately 4.6 billion years older than Earth. |
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pipeline_tag: text2text-generation |
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--- |
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## Model Details |
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- **Model Name**: English-Tamil-Translator |
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- **Model Type**: Deep Learning Model |
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- **Language**: Python |
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- **Task**: Language Translation |
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## How to Use |
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1. **Install Gemma Python Package**: |
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```bash |
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pip install -q -U transformers==4.38.0 |
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``` |
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## Inference |
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1. **How to use the model in our notebook**: |
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```python |
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# Load model directly |
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import torch |
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from transformers import AutoTokenizer, AutoModelForSeq2SeqLM |
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checkpoint = "Mr-Vicky-01/English-Tamil-Translator" |
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tokenizer = AutoTokenizer.from_pretrained(checkpoint) |
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model = AutoModelForSeq2SeqLM.from_pretrained(checkpoint) |
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def language_translator(text): |
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tokenized = tokenizer([text], return_tensors='pt') |
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out = model.generate(**tokenized, max_length=128) |
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return tokenizer.decode(out[0],skip_special_tokens=True) |
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text_to_translate = "i have to play football now!" |
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output = language_translator(text_to_translate) |
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print(output) |
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``` |
