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# Luganda to English Informal Translation Model |
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This model translates informal Luganda sentences to English. It was trained on a dataset of Luganda proverbs with their English translations. The dataset consists of 3135 examples. |
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## Data |
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**Train:** The training data consists of 3135 Luganda proverbs and their corresponding English translations. |
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**Eval:** The evaluation data is part of the training data and consists of informal sentences. |
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## Model |
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**Architecture:** Seq2Seq |
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**Pretrained Model:** Helsinki-NLP/opus-mt-ug-en |
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**Fine-tuning:** The model was fine-tuned for 50 epochs with a learning rate of 2e-5. |
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## Translation |
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**Source Language:** Luganda |
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**Target Language:** English |
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**Domain:** Informal sentences and proverbs |
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## Usage |
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Here is an example of how to load and use the model for translation: |
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```python |
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from transformers import AutoModelForSeq2SeqLM, AutoTokenizer |
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model_name = 'your_model_name_on_hf_hub' |
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model = AutoModelForSeq2SeqLM.from_pretrained(model_name) |
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tokenizer = AutoTokenizer.from_pretrained(model_name) |
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# Example input sentence in Luganda |
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input_sentence = 'Olutalo lwa nsi yonna lwazibwa omwaka oguwedde.' |
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inputs = tokenizer(input_sentence, return_tensors='pt') |
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outputs = model.generate(**inputs) |
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translation = tokenizer.decode(outputs[0], skip_special_tokens=True) |
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print(translation) |
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``` |
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