Text Classification
Transformers
PyTorch
Turkish
bert
Text Classification
Transformers
turkish
text-embeddings-inference
Instructions to use Marzu39/bert-turkish-text-classification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Marzu39/bert-turkish-text-classification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Marzu39/bert-turkish-text-classification")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Marzu39/bert-turkish-text-classification") model = AutoModelForSequenceClassification.from_pretrained("Marzu39/bert-turkish-text-classification", device_map="auto") - Notebooks
- Google Colab
- Kaggle
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README.md
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# Dataset
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The following Turkish dataset is used for fine-tuning
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https://huggingface.co/datasets/maydogan/TRSAv1
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# Load model directly
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# Citation
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Please cite the following paper if needed
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```python
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Arzu, M., & Aydoğan, M. (2023). Türkçe Duygu Sınıflandırma İçin Transformers Tabanlı Mimarilerin Karşılaştırılmalı Analizi. Computer Science, (IDAP-2023), 1-6.
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}
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```
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#### Summary
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# Dataset
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The following Turkish dataset is used for fine-tuning
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https://huggingface.co/datasets/maydogan/TRSAv1
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TRSAv1 (Turkish Sentiment Analysis Version 1) Dataset This data set has been produced to contribute to Turkish NLP studies. The dataset consists of a total of 150 thousand samples, 50 thousand negative, 50 thousand positive and 50 thousand neutral. It can be used in text classification and sentiment analysis studies by citing the related study.
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# Load model directly
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# Citation
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Please cite the following paper if needed
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#### Summary
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