tj-1.0

TJ-1.0

TJ-1.0 is the flagship instruction-tuned language model of the TajikGPT platform, developed by SoulLab. It is the first commercially deployed large language model with native support for the Tajik language, offering a balanced combination of quality, speed, and multilingual capability.

Note: TJ-1.0 is available via API only and is not available for download or local deployment.

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Model Details

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Training Data

TJ-1.0 was trained on a curated multilingual corpus with a strong emphasis on Tajik-language content — the first dataset of this scale built specifically for Tajik NLP.

Total corpus size: ~2 trillion tokens
Data freshness: Content up to Q3 2024
Processing: Deduplication, quality filtering, language identification, PII removal applied to all sources.

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Intended Use

Recommended Use Cases

• Multilingual chat and Q&A in Tajik, Russian, English and 50+ languages
• Document summarization and translation
• Creative writing, content creation and copywriting
• Education, tutoring and homework help
• Business communication and professional correspondence
• Data analysis, extraction and summarization
• Code generation and debugging

Out-of-Scope Use Cases

• Generation of illegal, harmful, or deceptive content
• Medical diagnosis or legal advice without professional oversight
• Surveillance or targeting of individuals
• Automated high-stakes decision-making without human review
• Any use violating the TajikGPT Terms of Service

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Evaluation / Benchmarks

All benchmarks were evaluated using standard few-shot settings unless otherwise noted.

General Benchmarks

Tajik Language Benchmarks

These are the first published benchmarks for Tajik-language LLM evaluation.

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How to Use

TJ-1.0 is available via the TajikGPT API. Install the SDK or use the REST API directly.

pip install tajikgpt

Python SDK

from tajikgpt import TajikGPT

client = TajikGPT(api_key="sk-tj-your-key")

response = client.chat.completions.create(
    model="tj-1.0",
    messages=[
        {"role": "system", "content": "Ты полезный помощник."},
        {"role": "user", "content": "Ба забони тоҷикӣ шарҳ деҳ: нейронӣ шабака чист?"}
    ]
)
print(response.choices[0].message.content)

REST API

curl -X POST https://tajikgpt.com/api/tj/chat \
  -H "Content-Type: application/json" \
  -H "Authorization: Bearer sk-tj-your-key" \
  -d '{
    "model": "tj-1.0",
    "messages": [
      {"role": "user", "content": "Hello! What can you do?"}
    ],
    "max_tokens": 1024,
    "temperature": 0.7
  }'

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Limitations

1. Dialectal Tajik: The model performs best on standard literary Tajik (Cyrillic). Regional dialects and Latin-script Tajik may show reduced quality.
2. Hallucinations: Like all LLMs, TJ-1.0 may generate plausible-sounding but factually incorrect information. Always verify critical facts.
3. Knowledge cutoff: The model has no knowledge of events after Q3 2024.
4. Mathematical reasoning: Complex multi-step calculations may produce errors. Use dedicated tools for precise math.
5. Low-resource languages: While 50+ languages are supported, quality varies significantly for lower-resource languages.
6. Long context degradation: Performance on tasks requiring reasoning over very long documents (>64K tokens) may degrade.

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Responsible AI & Safety

• RLHF: The model was fine-tuned using human preference data to align with helpful, harmless, and honest behavior.
• Red Teaming: Internal adversarial testing was conducted to identify failure modes in Tajik, Russian, and English.
• Content Filtering: The TajikGPT API includes a multi-layer content filtering system that operates independently of the model.
• Bias: Training data reflects the diversity of web content and may contain societal biases. Users should apply critical judgment when using outputs for sensitive decisions.
• Privacy: The training data was processed with PII (personally identifiable information) removal pipelines.

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Model Family

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Links

• Platform: tajikgpt.com
• API Docs: tajikgpt.com/docs
• Python SDK: pypi.org/project/tajikgpt
• Live Demo: HuggingFace Space
• Developer: SoulLab

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Citation

If you use TJ-1.0 in research or build products on top of it, please cite:

@misc{tajikgpt2024tj10,
  title        = {TJ-1.0: A Multilingual Large Language Model with Native Tajik Language Support},
  author       = {SoulLab},
  year         = {2024},
  howpublished = {\url{https://tajikgpt.com}},
  note         = {Proprietary model, available via API at https://tajikgpt.com}
}

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Built with care for Tajikistan and Central Asia. Developed by SoulLab.