Inference Optimization

Techniques for running models efficiently at inference time, from quantization to batching and sampling strategies.

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Inference

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Inference is the process of running a trained machine learning model to generate predictions, classifications, or text in real time. For large language models, inference involves autoregressive token generation, memory management through KV-cache, and careful balancing of latency against throughput to meet production requirements. Also known as: Model Inference, LLM Inference.

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