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sdk: gradio
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---
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title: BashkirNLP - Turkic & Low-Resource Languages
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emoji: 🏔️
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colorFrom: green
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colorTo: blue
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sdk: gradio
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pinned: true
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license: mit
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short_description: Bashkir & Turkic NLP for low-resource languages.
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sdk_version: 6.6.0
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---
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# BashkirNLP – Turkic & Low‑Resource Languages Research Hub
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**BashkirNLP** is a collaborative research initiative dedicated to advancing natural language processing for **Bashkir**, **Turkic languages**, and **low‑resource languages** in the Ural-Volga region and beyond. We develop state‑of‑the‑art language models, machine translation systems, linguistic resources, and educational tools to empower under‑represented languages in the digital age.
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---
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## 🎯 Our Mission
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- Build **open‑source language models** for Bashkir and other Turkic varieties (Tatar, Kazakh, Chuvash, etc.).
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- Create **high‑quality linguistic resources** (corpora, lexicons, evaluation benchmarks).
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- Advance **machine translation** between Bashkir, Russian, English, and major Turkic languages.
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- Develop **educational materials** and interactive demos to lower the entry barrier for low‑resource NLP.
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- Foster a community of researchers, developers, and native speakers working together on language technology.
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---
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## 🚀 Interactive Demos
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Explore our live Hugging Face Spaces and try out our models directly in your browser:
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### **🔤 Language Models**
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- **[BashkirGPT Playground]()** – Generate and analyze Bashkir text with our latest causal LM.
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- **[TurkicBERT Explorer]()** – Masked language modelling for Bashkir, Tatar, and other Turkic languages.
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- **[Multilingual Embeddings]()** – Compare word/sentence vectors across Turkic languages.
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### **🌐 Machine Translation**
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- **[Bashkir ↔ Russian Translator]()** – Neural translation between Bashkir and Russian.
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- **[Bashkir ↔ Tatar Translator]()** – Translation demo for closely related Turkic languages.
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- **[Bashkir ↔ English Translator]()** – Experimental translation for low-resource pairs.
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### **📚 Linguistic Tools**
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- **[Bashkir Morphological Analyzer]()** – Interactive segmentation and POS tagging (Cyrillic & Latin scripts).
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- **[Named Entity Recognition for Bashkir]()** – Identify persons, locations, organizations.
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- **[Script Converter]()** – Convert between Cyrillic Bashkir and Latin-based orthographies.
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### **📊 Data & Benchmarks**
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- **[Bashkir Corpus Explorer]()** – Browse and query our curated text collections.
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- **[Turkic NLP Leaderboard]()** – Compare model performance on Bashkir, Tatar, and other Turkic tasks.
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- **[Annotation Tools]()** – Help us improve datasets with your feedback.
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*Click on any demo to start experimenting – no installation required!*
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---
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## 🧠 Research Focus Areas
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### **🏞️ Bashkir Language Technologies**
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- Creation of the first large‑scale pretrained models for Bashkir (Cyrillic script, with Latin adaptation).
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- Morphological disambiguation and syntactic parsing for Bashkir (agglutinative morphology).
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- Speech recognition and synthesis for Bashkir (coming soon).
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### **📜 Turkic NLP**
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- Cross‑lingual transfer learning among Bashkir, Tatar, Kazakh, and other Kipchak languages.
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- Unified tokenization and subword models for the Turkic language family.
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- Machine translation between Turkic languages and major world languages.
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### **📉 Low‑Resource NLP**
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- Data augmentation and semi‑supervised learning techniques.
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- Leveraging multilingual models (e.g., mT5, XLM‑R, Turkmenglish) for under‑represented languages.
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- Few‑shot and zero‑shot learning for tasks like NER and sentiment analysis.
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### **🤖 Language Models**
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- Pretraining from scratch and continued pretraining on Bashkir/Turkic corpora.
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- Efficient architectures (ALBERT, DistilBERT) for low‑resource settings.
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- Evaluation and bias analysis of Turkic language models.
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### **📖 Linguistic Resources**
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- **Corpora**: News, literature, web‑crawled texts, social media (e.g., VK, Telegram).
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- **Lexicons**: Morphological dictionaries, wordnets, sentiment lexicons.
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- **Benchmarks**: Named entity recognition, part‑of‑speech tagging, machine translation test sets.
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---
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## 📦 Models & Datasets
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We release all our models and datasets on Hugging Face Hub under open licenses.
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| Model / Dataset | Description | Link |
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| **BashkirBERT** | BERT‑base model pretrained on Bashkir Cyrillic texts | [🤗 Hub]() |
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| **Turkic‑mT5** | Multilingual T5 fine‑tuned on Bashkir, Tatar, and Kazakh | [🤗 Hub]() |
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| **Bashkir‑MT‑BaRu** | Transformer��based translation model (Bashkir ↔ Russian) | [🤗 Hub]() |
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| **Bashkir‑NER** | Named entity recognition model for Bashkir | [🤗 Hub]() |
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| **BashkirCorpus v1.0** | 100M token corpus from news, books, and websites | [🤗 Dataset]() |
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| **Turkic‑Parallel‑Bench** | Parallel sentences for Bashkir, Tatar, and Turkish | [🤗 Dataset]() |
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*More models and datasets are added regularly. Follow our [organization page](https://huggingface.co/BashkirNLP) for updates.*
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---
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## 📚 Educational Resources
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We believe in **open education** and **reproducible research**. All our tutorials and teaching materials are freely available.
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- **[Interactive Notebooks]()** – Hands‑on tutorials for building low‑resource NLP systems (in Python, using Hugging Face libraries).
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- **[Video Lectures]()** – Recorded talks on Bashkir/Turkic NLP, data collection, and model training.
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- **[Course Materials]()** – Slides, readings, and assignments from our university courses.
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- **[Blog Posts]()** – Deep dives into challenges and solutions for Bashkir and Turkic languages.
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---
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## 📝 Selected Publications
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1. *"BashkirBERT: A Pretrained Language Model for Bashkir"* – LREC 2025 (planned)
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2. *"Machine Translation for Low-Resource Turkic Languages: Bashkir–Russian Case Study"* – WMT 2024
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3. *"Building a Named Entity Recognition Dataset for Bashkir"* – TurkicLang 2024
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4. *"Multilingual Representations for Kipchak Languages: A Comparative Study"* – EMNLP 2023
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5. *"Bashkir Corpus: Collection, Annotation, and Baseline Experiments"* – Dialogue 2023
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*Full list with links to PDFs available on our [Publications Page]().*
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---
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## 🤝 Get Involved
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We welcome contributions from the community – whether you are a researcher, developer, student, or native speaker.
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### **For Researchers**
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- Use our models and datasets in your work (and cite us!).
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- Collaborate on joint papers and grant proposals.
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- Contribute new benchmarks or evaluation tasks.
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### **For Developers**
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- Integrate our models into your applications.
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- Report bugs or suggest improvements via GitHub Issues.
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- Submit pull requests to our open‑source repositories.
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### **For Native Speakers & Linguists**
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- Help us validate translations and annotations.
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- Share texts or corpora (with permission) to enrich our data.
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- Provide feedback on model outputs to reduce errors.
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### **For Students**
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- Use our demos and tutorials for learning.
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- Participate in our mentorship program or summer schools.
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- Start your own research project with our support.
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---
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## 🌐 Connect With Us
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- **🤗 Hugging Face**: [BashkirNLP](https://huggingface.co/BashkirNLP) – Models, datasets, and spaces.
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- **💻 GitHub**: [BashkirNLP](https://github.com/BashkirNLP) – Source code, development, and issue tracking.
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- **📧 Email**: [contact@bashkirnlp.org](mailto:contact@bashkirnlp.org) – General inquiries and collaboration.
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- **📝 Blog**: [Medium/BashkirNLP](https://medium.com/bashkirnlp) – In‑depth articles.
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## 🔄 Ecosystem Integration
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Our work is integrated with the broader Hugging Face ecosystem:
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- **Models** on the Hub with easy‑to‑use pipelines.
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- **Datasets** with streaming and evaluation scripts.
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- **Spaces** for interactive demos and educational tools.
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- **Gradio** apps for user‑friendly interfaces.
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---
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**Empowering Bashkir and Turkic languages through open science and community collaboration.**
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<div align="center">
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[](https://huggingface.co/BashkirNLP)
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[](https://github.com/BashkirNLP)
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[](https://twitter.com/BashkirNLP)
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**© 2026 BashkirNLP** – Open source for low‑resource languages.
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