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I was going to ask the same exact thing.Maybe I am just being an idiot today, but what is this, and what does it do?
Local AI is different. A model is only one part of the system. To find the best setup for your workload, you have to make several choices together.
Getting the best combination should not require becoming an expert in every one of these layers.
- Which model suits the workload?
- Which hardware should run it?
- Which agent harness should you use?
- Which inference engine should serve it?
- Which model variation, quantization or pruning method should you use?
- Which runtime configuration should you choose, such as speculative decoding?