What are the hardware requirements for Bert Base Turkish Cased?

Bert Base Turkish Cased requires approximately 0.4 GB of VRAM and supports a context window of 0.5K tokens. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed Bert Base Turkish Cased and how large is it?

Bert Base Turkish Cased is developed by dbmdz, a model with 111.2m parameters. The model is published as open weights on Hugging Face and indexed on LLM Explorer with full benchmark history.

Where can I download or evaluate Bert Base Turkish Cased?

Bert Base Turkish Cased is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

Bert Base Turkish Cased by dbmdz — VRAM 0.4GB, 0.5K context

Name: Bert Base Turkish Cased
Author: dbmdz

Bert Base Turkish Cased is an open-source language model by dbmdz. Features: 111.2m LLM, VRAM: 0.4GB, Context: 0.5K, License: mit, LLM Explorer Score: 0.07.

Bert Endpoints compatible Jax Pytorch Region:us Safetensors Tf Tr

Model Card on HF 🤗: https://huggingface.co/dbmdz/bert-base-turkish-cased

Bert Base Turkish Cased Parameters and Internals

Model Type

text processing

Use Cases

Areas:

Research

Applications:

NLP tasks like PoS tagging, NER

Additional Notes

The BERTurk model is available on Hugging Face model hub.

Supported Languages

Turkish (Proficient)

Training Details

Data Sources:

Turkish OSCAR corpus, Wikipedia dump, OPUS corpora, Corpus by Kemal Oflazer

Data Volume:

44,04,976,662 tokens

Methodology:

Pre-trained using BERT infrastructure

Hardware Used:

TPU v3-8

Release Notes

Notes:

Initial release of BERTurk cased model for Turkish.

LLM Name	Bert Base Turkish Cased
Repository 🤗	https://huggingface.co/dbmdz/bert-base-turkish-cased
Model Size	111.2m
Required VRAM	0.4 GB
Updated	2026-08-07
Maintainer	dbmdz
Model Type	bert
Model Files	0.4 GB 0.4 GB
Supported Languages	tr
Model Architecture	AutoModel
License	mit
Context Length	512
Model Max Length	512
Vocabulary Size	32000

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Instruction Following and Task Automation
Factuality and Completeness of Knowledge
Censorship and Alignment
Data Analysis and Insight Generation
Text Generation
Text Summarization and Feature Extraction
Code Generation
Multi-Language Support and Translation