Instructions to use ubayram/ConspiracyTurk with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ubayram/ConspiracyTurk with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="ubayram/ConspiracyTurk")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("ubayram/ConspiracyTurk") model = AutoModelForSequenceClassification.from_pretrained("ubayram/ConspiracyTurk") - Notebooks
- Google Colab
- Kaggle
Update README.md
Browse files
README.md
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base_model:
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- dbmdz/bert-base-turkish-cased
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language:
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- tr
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library_name: transformers
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license: cc-by-4.0
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pipeline_tag: text-classification
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---
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# Model Card For ConspiracyTurk
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This model is created by fine-tuning the famous BERTurk model that was already pretrained to work on
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Turkish language. Fine-tuned to detect belief in conspiracy from Turkish texts.
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The model is fine-tuned using social media posts.
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- **Developed by:** Dr. Ulya BAYRAM
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- **Model type:** Classification
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- **License:** Creative Commons
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- **Finetuned from model:** BERTurk
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## How to Get Started with the Model
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Use the code below to get started with the model.
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[More Information Needed]
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## Training Data
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To train this model, a private data collection scraped from social media, and then manually labeled by experts is used.
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The dataset is available to researchers per demand with the conditions of using it only for research purposes and not sharing it with others.
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## Model Source and Citation
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<!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
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When using this model for your research, please cite the following paper, which is the source of the model:
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**Paper:** [More Information Needed]
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**BibTeX:**
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[More Information Needed]
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**APA:**
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[More Information Needed]
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