Instructions to use oguzhanolm/loodos-bert-base-uncased-QA-fine-tuned with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use oguzhanolm/loodos-bert-base-uncased-QA-fine-tuned with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("question-answering", model="oguzhanolm/loodos-bert-base-uncased-QA-fine-tuned")# Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("oguzhanolm/loodos-bert-base-uncased-QA-fine-tuned") model = AutoModelForQuestionAnswering.from_pretrained("oguzhanolm/loodos-bert-base-uncased-QA-fine-tuned", device_map="auto") - Notebooks
- Google Colab
- Kaggle
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README.md
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# Turkish SQuAD Model : Question Answering
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I fine-tuned Loodos-Turkish-Bert-Model for Question-Answering problem with TQuAD dataset
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* Loodos-BERT-base: https://huggingface.co/loodos/bert-base-turkish-uncased
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* TQuAD dataset: https://github.com/TQuad/turkish-nlp-qa-dataset
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# Turkish SQuAD Model : Question Answering
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I fine-tuned Loodos-Turkish-Bert-Model for Question-Answering problem with TQuAD dataset. Since the "loodos/bert-base-turkish-uncased" model gave the best results for the Turkish language in classification in the "Auto-tagging of Short Conversational Sentences using Transformer Methods" research we conducted with my teammates, I used this model because I thought that the success rate could be high in the question-answering.
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* Loodos-BERT-base-uncased: https://huggingface.co/loodos/bert-base-turkish-uncased
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* TQuAD dataset: https://github.com/TQuad/turkish-nlp-qa-dataset
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