Instructions to use anilguven/albert_tr_qa_turkish_squad with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use anilguven/albert_tr_qa_turkish_squad with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("question-answering", model="anilguven/albert_tr_qa_turkish_squad")# Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("anilguven/albert_tr_qa_turkish_squad") model = AutoModelForQuestionAnswering.from_pretrained("anilguven/albert_tr_qa_turkish_squad", device_map="auto") - Notebooks
- Google Colab
- Kaggle
metadata
license: mit
language:
- tr
metrics:
- accuracy
- f1
pipeline_tag: question-answering
tags:
- qa
- question answering
- squad
- albert
Information
This model was developed/finetuned for QA task for the Turkish Language. This model was finetuned via Turkish SQuAD dataset.
Model Sources
- Dataset: https://github.com/boun-tabi/SQuAD-TR
- Paper: peer review (Springer)
- Finetuned from model: https://huggingface.co/loodos/albert-base-turkish-uncased
Results
- Accuracy: %71.58
Citation
BibTeX: Peer review process