t is Open-source and accessible on Hugging Face under Apache 2.0.
The Enterprise-focus with full transparency about the quality of the training data.
Scalable models in various parameter sizes for customizable trade-offs between performance and accuracy.
Specialized variants for code, time series, geospatial, and translation tasks.
Fully deployable behind firewalls on Ollama on Linux for secure, stand-alone operation.
We currently use MOE (Mixture of Experts) and dense models, with plans to integrate Instruct models in LangChain setups for context-rich company document processing.
What Could Be Better?
Requires notable prompt tuning for consistent, relevant results.
English-to-SQL translation is decent but still needs a DBA’s fine-tuning.
Being new, the models lack extensive usage history, meaning you’ll need to experiment and adapt.
What Problems Is IBM Granite Tackling?
Streamlining code assistance for non-DBAs.
Enhancing failure prediction during product testing.
Optimizing workload batching for smoother production processes.
I feel that these efficient, adaptable, and enterprise-friendly, IBM Granite 3 models are setting the stage for robust AI-driven solutions.