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emresallak/
bert-turkish-biomedical

Name: bert-turkish-biomedical
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Model Card for emresallak/bert-turkish-biomedical

Model Description

This model is a Turkish biomedical BERT model fine-tuned for natural language processing tasks in the biomedical domain.

It is based on a pre-trained Turkish BERT model and adapted to better understand domain-specific terminology such as medical concepts, clinical language, and biomedical text.

Developed by: emresallak
Model type: BERT
Language(s): Turkish
License: apache-2.0 (recommended, change if different)
Finetuned from model: dbmdz/bert-base-turkish-cased

Model Sources

Repository: https://huggingface.co/emresallak/bert-turkish-biomedical

Uses

Direct Use

This model can be used for Turkish biomedical NLP tasks such as:

Text classification
Named entity recognition (NER)
Semantic understanding of medical text

Downstream Use

The model can be further fine-tuned for specific tasks like:

Clinical text classification
Medical entity extraction
Question answering in the biomedical domain

Out-of-Scope Use

This model should NOT be used for:

Medical diagnosis
Clinical decision-making
Any real-world healthcare application without expert validation

Bias, Risks, and Limitations

The model inherits biases from the original training data
Biomedical datasets may contain incomplete or domain-specific biases
Performance may degrade on:
- Non-biomedical Turkish text
- Informal language
- Out-of-distribution inputs

Recommendations

Users should:

Validate outputs before real-world use
Avoid using the model in high-stakes scenarios
Perform task-specific fine-tuning when possible

How to Get Started with the Model

python

from transformers import AutoTokenizer, AutoModel

tokenizer = AutoTokenizer.from_pretrained("emresallak/bert-turkish-biomedical")
model = AutoModel.from_pretrained("emresallak/bert-turkish-biomedical")