Instructions to use buddhist-nlp/mt5-600M-tib2eng with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use buddhist-nlp/mt5-600M-tib2eng with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("buddhist-nlp/mt5-600M-tib2eng") model = AutoModelForSeq2SeqLM.from_pretrained("buddhist-nlp/mt5-600M-tib2eng") - Notebooks
- Google Colab
- Kaggle
| Training setup | |
|---|---|
| Num train steps | 10000 |
| Max seq len | 256 |
| Batch size | 512 |
| Total data points seen | 5.1 mil |
| Total tokens seen | 450 mil |
| Checkpoint step | 9800 |
| Learning rate | 2e-3 |
| Metric | Val | Test |
|---|---|---|
| BLEU | 25.6 | 23.5 |
| chrf++ | 44.3 | 42.8 |
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