T3 Gemstone O1 edge models: NanoSOC, person/object detection, local face identity, exports, evaluations, and deployment assets.
Göktuğ Düşünen PRO
GoktugD
AI & ML interests
Head of AI @ Werea · AI/ML Engineer
AI/ML Engineer building end-to-end intelligent systems across LLMs, NLP, Computer Vision, RAG, Retrieval, Agents, and Applied AI.
From data and model development to fine-tuning, evaluation, optimization, deployment, and production AI systems.
Recent Activity
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Werea-co/Werea-TR-TextRestore:Demo for this model on Spaces new activity 2 days ago
Werea-co/Werea-TR-TextRestore:Demo for this model on Spaces posted an update 2 days ago
🇹🇷 **A 1B Turkish OCR model vs. Baidu OCR.**
We ran both models on the **same Turkish enterprise documents**.
The result:
**Werea-DocOCR-1B → 99.9**
**Baidu Unlimited-OCR → 47.9**
Same documents.
Same evaluation.
And Werea-DocOCR is only **1B parameters**.
It was built specifically for difficult Turkish enterprise documents:
📄 invoices
📑 contracts
🏦 bank receipts
💼 payroll
🚗 vehicle documents
📋 SGK-style tables
📱 scanned & phone-captured documents
But benchmarks aren't enough.
**Give me a Turkish document that you think will break it.**
We'll test the hardest ones and publish the failures.
🤗 Model:
https://huggingface.co/Werea-co/Werea-DocOCR-1B
📚 Dataset:
https://huggingface.co/datasets/Werea-co/werea-tr-doc-ocr-enterprise-v2
🇹🇷 Built in Türkiye. Open on Hugging Face.
#OCR #DocumentAI #HuggingFace #TurkishAI
Organizations
T3 Gemstone O1 edge models: NanoSOC, person/object detection, local face identity, exports, evaluations, and deployment assets.
Public 2B and 4B GGUF security operations models for T3 Gemstone-class ARM edge boards.
Werea'nın Türkçe TTS ailesi: 183M ve 1.7B modeller, sentetik eğitim verisi ve demo. Etik sentetik ses — klonlama yok.
Open Turkish AI by Göktuğ Düşünen: OCR, speech, text restoration, embeddings, reranking, benchmarks and live demos.