Instructions to use Wikidepia/indobert-lite-squadx with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Wikidepia/indobert-lite-squadx with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("question-answering", model="Wikidepia/indobert-lite-squadx")# Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("Wikidepia/indobert-lite-squadx") model = AutoModelForQuestionAnswering.from_pretrained("Wikidepia/indobert-lite-squadx") - Notebooks
- Google Colab
- Kaggle
IndoBERT-Lite-SQuAD base fine-tuned on Full Translated SQuAD v2
IndoBERT-Lite trained by Indo Benchmark and fine-tuned on Translated SQuAD 2.0 for Q&A downstream task.
Model in action
Fast usage with pipelines:
from transformers import BertTokenizerFast, pipeline
tokenizer = BertTokenizerFast.from_pretrained(
'Wikidepia/indobert-lite-squad'
)
qa_pipeline = pipeline(
"question-answering",
model="Wikidepia/indobert-lite-squad",
tokenizer=tokenizer
)
qa_pipeline({
'context': "Setelah menghabiskan waktu satu tahun di Praha, Einstein tinggal di Swiss antara tahun 1895 dan 1914, melepas kewarganegaraan Jermannya pada tahun 1896, dan lulus sarjana dari sekolah politeknik federal Swiss (kelak Eidgenössische Technische Hochschule, ETH) di Zürich pada tahun 1900.",
'question': "Kapan Einstein melepas kewarganegaraan Jerman?"
})
Output:
{
"score": 0.9169162511825562,
"start": 147,
"end": 151,
"answer": "1896"
}
README copied from mrm8488's repository
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