How do you optimize LLMs for low-latency applications?
Answer / Uday Veer
To optimize Langauge Models (LLMs) for low-latency applications, consider the following practices: 1. Model pruning to remove unnecessary parameters; 2. Quantization techniques like weight quantization and model quantization to reduce computational requirements; 3. Using efficient hardware like GPUs or TPUs; 4. Implementing online training or online fine-tuning that updates the model as new data comes in, reducing latency associated with loading pre-trained models; 5. Caching previous outputs to minimize repeated computation.
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