Translation
Transformers
Safetensors
English
Tamil
m2m_100
text2text-generation
english-to-tamil
tamil
machine-translation
nllb
multilingual
Instructions to use Deepak1206/english-tamil-translator with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Deepak1206/english-tamil-translator with Transformers:
# Use a pipeline as a high-level helper # Warning: Pipeline type "translation" is no longer supported in transformers v5. # You must load the model directly (see below) or downgrade to v4.x with: # 'pip install "transformers<5.0.0' from transformers import pipeline pipe = pipeline("translation", model="Deepak1206/english-tamil-translator")# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("Deepak1206/english-tamil-translator") model = AutoModelForSeq2SeqLM.from_pretrained("Deepak1206/english-tamil-translator", device_map="auto") - Notebooks
- Google Colab
- Kaggle
English โ Tamil Translation Model ๐ฌ๐ง โ ๐ฎ๐ณ
๐ Overview
This project provides an English-to-Tamil neural machine translation model based on Meta AI's NLLB-200 architecture.
The model takes English text as input and generates the corresponding Tamil translation.
Pipeline
English Text โ NLLB-200 Translation Model โ Tamil Text
โจ Features
- English โ Tamil translation
- Neural machine translation
- Supports long-form text
- Uses the NLLB-200 multilingual architecture
- Easy integration using Hugging Face Transformers
- Can be used directly through Python
๐ค Model Information
Base Model
facebook/nllb-200-distilled-600M
Architecture
NLLB-200 Distilled Seq2Seq Transformer
Source Language
English (eng_Latn)
Target Language
Tamil (tam_Taml)
๐ Usage
Install the required libraries:
pip install transformers sentencepiece torch
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