Databricks has created a new state-of-the-art open-source large language model (LLM) called DBRX. DBRX surpasses established open models on various benchmarks, including code, math, and general language understanding. Here's a breakdown of the key points:
What is DBRX?
- Transformer-based decoder-only LLM trained with next-token prediction
- Fine-grained mixture-of-experts (MoE) architecture (132B total parameters, 36B active parameters)
- Pretrained on 12 trillion tokens of carefully curated text and code data
- Uses rotary position encodings (RoPE), gated linear units (GLU), and grouped query attention (GQA)
- Achieves high performance on long-context tasks and RAG (Retrieval-Augmented Generation)
How does DBRX compare?
- Outperforms GPT-3.5 on most benchmarks and is competitive with closed models like Gemini 1.0 Pro
- Achieves higher quality scores on code (HumanEval) and math (GSM8k) compared to other open models
Benefits of DBRX
- Open-source and available for download and fine-tuning
- Efficient training process (4x less compute compared to previous models)
- Faster inference compared to similar-sized models due to MoE architecture
- Integrates with Databricks tools and services for easy deployment
Getting Started with DBRX
- Available through Databricks Mosaic AI Foundation Model APIs (pay-as-you-go)
- Downloadable from Databricks Marketplace for private hosting
- Usable through Databricks Playground chat interface
Future of DBRX
- Expected advancements and new features in the future
- DBRX serves as a foundation for building even more powerful and efficient LLMs
Overall, DBRX is a significant development in the field of open LLMs, offering high-quality performance, efficient training, and ease of use.
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