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DBRX is a large language model (LLM) developed by Mosaic under its parent company Databricks, released on March 27, 2024 under the Databricks Open Model License. It is a mixture-of-experts transformer model, with 132 billion parameters in total. 36 billion parameters (4 out of 16 experts) are active for each token. The released model comes in either a…
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Explore the main themes, entities and connections around DBRX. Start with the topic map, then use the sections below for research and deeper semantic analysis.
Start with a few of the strongest sections from the source topic. These are research directions, not a list of keywords you must use.
High-confidence facts extracted from structured source data. Use them as anchors for further research.
Browse the full topic structure. Each item opens a new analysis centered on that subject.
Deeper signals for content research, entity SEO and topical coverage. The plain-language headings explain what each technical view is useful for.
See the strongest relationship patterns around the current topic before diving into the raw triples.
Use these terms to understand the vocabulary surrounding the topic, not as a checklist for keyword stuffing.
model databricks language released billion parameters mosaic open license release mixture-of-experts transformer instruction-tuned grok-1 infiniband large llm developed parent company
| Subject | Predicate | Object | Confidence | Src |
|---|---|---|---|---|
| DBRX | Developers | Mosaic ML and Databricks team | 1.00 | infobox |
| DBRX | License | Databricks Open Model License | 1.00 | infobox |
| DBRX | Release | March 27, 2024 | 1.00 | infobox |
| DBRX | Repository | https://github.com/databricks/dbrx | 1.00 | infobox |
| DBRX | Website | https://www.databricks.com/blog/introducing-dbrx-new-state-art-open-llm | 1.00 | infobox |
| DBRX | is a | large language model | 0.90 | text |
| Meta's Llama 2 | instance of | DBRX outperformed prominent models | 0.80 | text |
| Mistral AI's Mixtral | instance of | DBRX outperformed prominent models | 0.80 | text |
| and xAI's Grok-1 | instance of | DBRX outperformed prominent models | 0.80 | text |
| in several benchmarks ranging from language understanding | instance of | DBRX outperformed prominent models | 0.80 | text |
| programming ability | instance of | DBRX outperformed prominent models | 0.80 | text |
| mathematics.It was trained for 2.5 months | instance of | DBRX outperformed prominent models | 0.80 | text |
These clusters group vocabulary that occurs around closely connected concepts in the source material.
Bridges can reveal useful research angles that are easy to miss in a flat list of related terms.