Falcon-11B
| Property | Value |
|---|---|
| Parameter Count | 11.1B |
| Training Tokens | 5,000B |
| Context Length | 8,192 tokens |
| Languages | 10 (including English, German, French, etc.) |
| License | TII Falcon License 2.0 |
| Paper | Technical Report |
What is falcon-11B?
Falcon-11B is a powerful causal decoder-only language model developed by TII (Technology Innovation Institute). It represents a significant advancement in multilingual language modeling, trained on over 5,000B tokens from RefinedWeb and other curated corpora. The model supports 10 European languages and is designed for research and specialized applications through fine-tuning.
Implementation Details
The model employs advanced architectural features including rotary positional embeddings, multiquery attention, and FlashAttention-2. It was trained using a sophisticated 3D parallelism strategy across 1024 A100 GPUs, implementing BF16 precision and AdamW optimization.
- 60 layers with 4096 dimension model
- 8192 token context length
- Trained in four distinct stages for optimal performance
- Implements Flash-Attention 2 for improved efficiency
Core Capabilities
- Multilingual text generation across 10 European languages
- Strong performance on various benchmarks (59.73% on ARC-Challenge-25shots)
- Suitable for research and specialized fine-tuning
- Efficient processing with 8K context window
Frequently Asked Questions
Q: What makes this model unique?
Falcon-11B stands out for its efficient architecture combining multiquery attention with Flash-Attention 2, extensive training on 5,000B tokens, and support for 10 European languages. It achieves impressive benchmark scores while maintaining a relatively compact size compared to larger models.
Q: What are the recommended use cases?
The model is best suited for research purposes and as a foundation for fine-tuning in specific applications. It excels in text generation, summarization, and conversational tasks, but should be fine-tuned with appropriate guardrails for production use.
