mbazaNLP/NMT_Education_parallel_data_en_kin
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How to use DigitalUmuganda/Nllb_finetuned_education_en_kin with Transformers:
# Load model directly
from transformers import AutoTokenizer, AutoModelForSeq2SeqLM
tokenizer = AutoTokenizer.from_pretrained("DigitalUmuganda/Nllb_finetuned_education_en_kin")
model = AutoModelForSeq2SeqLM.from_pretrained("DigitalUmuganda/Nllb_finetuned_education_en_kin")This is a Machine Translation model, finetuned from NLLB-200's distilled 1.3B model, it is meant to be used in machine translation for education-related data.
Use the code below to get started with the model.
The model was finetuned on three datasets; a general purpose dataset, a tourism, and an education dataset.
The model was finetuned in two phases.
Other than the dataset changes between phase one, and phase two finetuning; no other hyperparameters were modified. In both cases, the model was trained on an A100 40GB GPU for two epochs.
Model performance was measured using BLEU, spBLEU, and chrF++ metrics.