Instructions to use werent4/mt5TranslatorLT with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use werent4/mt5TranslatorLT with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("werent4/mt5TranslatorLT") model = AutoModelForSeq2SeqLM.from_pretrained("werent4/mt5TranslatorLT") - Notebooks
- Google Colab
- Kaggle
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README.md
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It was trained on the following datasets:
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* [ted_talks_iwslt](https://huggingface.co/datasets/IWSLT/ted_talks_iwslt)
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* [werent4/lithuanian-translations](https://huggingface.co/datasets/werent4/lithuanian-translations)
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Other languages will also be added in the future.
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## Model Usage
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It was trained on the following datasets:
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* [ted_talks_iwslt](https://huggingface.co/datasets/IWSLT/ted_talks_iwslt)
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* [werent4/lithuanian-translations](https://huggingface.co/datasets/werent4/lithuanian-translations)
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* [scoris/en-lt-merged-data](https://huggingface.co/datasets/scoris/en-lt-merged-data)
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## Model Usage
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