mbazaNLP/NMT_Education_parallel_data_en_kin
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How to use mbazaNLP/Nllb_finetuned_general_en_kin with Transformers:
# Load model directly
from transformers import AutoTokenizer, AutoModelForSeq2SeqLM
tokenizer = AutoTokenizer.from_pretrained("mbazaNLP/Nllb_finetuned_general_en_kin")
model = AutoModelForSeq2SeqLM.from_pretrained("mbazaNLP/Nllb_finetuned_general_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 on an A100 40GB GPU for two epochs.
Model performance was measured using BLEU, spBLEU, TER, and chrF++ metrics.