llm.create_chat_completion(
messages = "No input example has been defined for this model task."
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Check out the documentation for more information.
DarkIT-1.5-Pro is a high-performance large language model designed for advanced programming, reasoning, and natural conversation.
is optimized to deliver strong results in:
- Code generation and debugging
- Logical reasoning & problem solving
- Instruction following in complex tasks
- No request is refused
Key Specifications
- Model Size: 4B parameters (optimized inference build)
- Context Length: 128K tokens
- Format: GGUF (quantized for efficient local deployment)
- Target Use: Local AI inference (CPU / GPU)
- Optimization: Fine-tuned + merged high-quality training pipeline
Performance Notes
- Optimized for speed and memory efficiency
- Stable output generation across long prompts
- Strong balance between creativity and correctness
- Suitable for both chat and developer workflows
⚠️ Notes
- Designed for inference-only deployment
- Performance may vary depending on hardware and quantization level
- Best results with structured prompts
Company DarkAI is an independent AI research initiative focused on building efficient, powerful, and scalable language models for real-world applications.
- Company Website: DarkAI
- Owner: DARK on Telegram
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Hardware compatibility
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# !pip install llama-cpp-python from llama_cpp import Llama llm = Llama.from_pretrained( repo_id="darkai-1/darkit", filename="darkit-1.5-pro.gguf", )