int8 — 质量和大小之间的平衡。质量损失极小（约 1~3%），文件大小比 FP16 减少约 2 倍。
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Like the N-convex algorithm, this algorithm attempts to find a set of candidates whose centroid is close to . The key difference is that instead of taking unique candidates, we allow candidates to populate the set multiple times. The result is that the weight of each candidate is simply given by its frequency in the list, which we can then index by random selection: