Model Detail
Turkish-Gemma-9b-T1
—Turkish-Gemma-9b-T1 is a large language model with 9B parameters released by ytu-ce-cosmos. The model is registered under the text-generation pipeline tag on Hugging Face.
Turkish-Gemma-9b-T1 ships with 9B parameters.
Turkish-Gemma-9b-T1 is best fit for general-purpose chat and instruction-following workloads. Treat this as a starting matrix rather than a benchmark verdict — the right deployment usually depends on the specific evaluation suite that mirrors your workload.
SarcasTraps: Effect of Sarcasm on Turkish Hate Speech Detection
arXiv:2610.16957v1 Announce Type: cross Abstract: Standard hate speech detection datasets often emphasize explicit harmful language, but directed harm can also be expressed indirectly, without clearly hateful wording. Sarcasm is one such form of indirect expression, as it can convey harmful intent t
TabiBERT: A Large-Scale ModernBERT Foundation Model and A Unified Benchmark for Turkish
arXiv:2512.23065v4 Announce Type: replace Abstract: The introduction of BERT established encoder-only transformer models as a foundational paradigm in natural language processing. Encoder-only models remain the standard tool for classification, tagging and retrieval, where contextual representations
HakemBench: A Turkish Benchmark of Typed Decisions
arXiv:2610.02293v1 Announce Type: new Abstract: HakemBench is a Turkish benchmark of typed decisions, in which the model under test reads a text, a question and a fixed set of options and returns a probability for every option. Version 1.0 is released fully open under CC BY 4.0, with 2,346 items and
Morpheus: A Morphology-Aware Neural Tokenizer and Word Embedder for Turkish
arXiv:2606.18717v2 Announce Type: replace-cross Abstract: Turkish is agglutinative: meaning is carried by morphemes, yet the subword tokenizers that drive modern language models split words by corpus statistics, fragmenting semantically loaded suffixes and -- in the case of WordPiece and rule-based
Evaluating Open-Weight LLMs for Turkish Domain Documents Under Retrieval and Hardware Constraints
arXiv:2609.28007v1 Announce Type: new Abstract: Most Turkish-capable large language models (LLMs) are evaluated using general-purpose benchmarks rather than long, structurally complex domain documents. This paper evaluates five open-weight 7B-8B models for Turkish document question answering under a
ufakzeka-1: Building and Evaluating a 151M-Parameter Turkish Language Model from Scratch
arXiv:2609.25081v1 Announce Type: new Abstract: We describe ufakzeka-1, a 151M-parameter (182M with embeddings) decoder-only Turkish language model pretrained from scratch on 13.5B tokens of openly licensed text and instruction-tuned for chat, at a total cost of about \$286 in cloud GPU, API and not
