Falcon3-10B-Instruct
| Property | Value |
|---|---|
| Parameter Count | 10 Billion |
| Context Length | 32K tokens |
| Languages | English, French, Spanish, Portuguese |
| License | TII Falcon-LLM License 2.0 |
| Release Date | December 2024 |
What is Falcon3-10B-Instruct?
Falcon3-10B-Instruct is a state-of-the-art instruction-tuned language model developed by Technology Innovation Institute (TII). It represents a significant advancement in the Falcon3 family, trained on 2 Teratokens of diverse datasets and fine-tuned on 1.2 million samples of specialized content including STEM, conversational, code, and safety data.
Implementation Details
The model features a transformer-based causal decoder-only architecture with 40 decoder blocks, implementing Grouped Query Attention (GQA) for efficient inference. It utilizes advanced features like SwiGLU activation and RMSNorm, with a high RoPE value of 1000042 for enhanced long-context understanding.
- 12 query heads and 4 key-value heads for optimized attention
- 256-dimension head width for improved processing
- 131K vocabulary size
- Training conducted on 1024 H100 GPU chips
Core Capabilities
- Exceptional performance in reasoning tasks (78.17% on IFEval)
- Strong mathematical abilities (25.91% on MATH Level-5)
- Advanced STEM and technical understanding
- Multilingual support across four languages
- Code generation and analysis capabilities
- Long context processing up to 32K tokens
Frequently Asked Questions
Q: What makes this model unique?
The model stands out for its exceptional performance on technical and reasoning tasks, outperforming many larger models on benchmarks like IFEval and BBH. Its architecture is specifically optimized for STEM applications while maintaining strong general-purpose capabilities.
Q: What are the recommended use cases?
Falcon3-10B-Instruct excels in technical applications, including mathematical problem-solving, scientific reasoning, and code generation. It's particularly well-suited for educational applications, research assistance, and multilingual technical documentation.
