Fibonacci-2-14B
Property | Value |
---|---|
Parameter Count | 14 billion |
Architecture | Phi 4 |
License | MIT |
Formats | GGUF (4-bit, 5-bit, 8-bit, 16-bit) |
Model URL | huggingface.co/fibonacciai/fibonacci-2-14B |
What is fibonacci-2-14B?
Fibonacci-2-14B is a sophisticated large language model built on the Phi 4 architecture, featuring 14 billion parameters. It represents a significant advancement in natural language processing capabilities, designed specifically for versatile text processing and generation tasks. The model stands out for its multi-format support and optimization for practical applications.
Implementation Details
The model is implemented using the advanced Phi 4 architecture and offers multiple quantization options through GGUF format, including 4-bit (Q4_K_M), 5-bit (Q5_K_M), 8-bit (Q8_0), and 16-bit (F16) variants. This flexibility allows users to balance performance and resource requirements based on their specific needs.
- Comprehensive parameter optimization with 14B parameters
- Multiple quantization formats for deployment flexibility
- Built on the efficient Phi 4 architecture
- Hugging Face Transformers library integration
Core Capabilities
- Advanced text generation and creative content creation
- Robust question-answering capabilities
- Machine translation between multiple languages
- Sentiment analysis and emotion detection in text
- Natural language understanding and processing
Frequently Asked Questions
Q: What makes this model unique?
The model's combination of the Phi 4 architecture with 14B parameters, along with its multi-format support and optimization for various NLP tasks, makes it particularly versatile. The availability of different quantization options allows for flexible deployment across different computing environments.
Q: What are the recommended use cases?
The model excels in text generation, question-answering, machine translation, and sentiment analysis tasks. It's particularly well-suited for applications requiring creative content generation, multilingual support, and advanced natural language understanding.