Ik45/wikipedia_dataset_science_en_id
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How to use Ik45/mt-science-en-id-finetuning with Transformers:
# Use a pipeline as a high-level helper
# Warning: Pipeline type "translation" is no longer supported in transformers v5.
# You must load the model directly (see below) or downgrade to v4.x with:
# 'pip install "transformers<5.0.0'
from transformers import pipeline
pipe = pipeline("translation", model="Ik45/mt-science-en-id-finetuning") # Load model directly
from transformers import AutoTokenizer, AutoModelForSeq2SeqLM
tokenizer = AutoTokenizer.from_pretrained("Ik45/mt-science-en-id-finetuning")
model = AutoModelForSeq2SeqLM.from_pretrained("Ik45/mt-science-en-id-finetuning")This model is a fine-tuned version of the pre-trained Helsinki-NLP/opus-mt-en-id (MarianMT) model. It has been specifically trained to improve translation quality from English to Indonesian, focusing on [sebutkan fokus domain Anda di sini, misal: domain sains / percakapan sehari-hari / dact dataset].
Helsinki-NLP/opus-mt-en-iden)id)This model is intended for direct text translation from English to Indonesian.
You can easily use this model with the Hugging Face transformers library.
pipeline
from transformers import pipeline
# Load the fine-tuned model
translator = pipeline("translation", model="Ik45/marianMT-en-id-dact-finetuning")
text = "Quantum mechanics is a fundamental theory in physics."
result = translator(text)
print(result[0]['translation_text'])
Base model
Helsinki-NLP/opus-mt-en-id