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- 扩大模型名称检测范围，匹配所有 deepseek 模型（V4、R1 等） - 始终保留 thinking blocks 为 reasoning_content 回传给 API - 移除有 bug 的 turn boundary 剥离逻辑 Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>
15 lines
555 B
Markdown
15 lines
555 B
Markdown
# Learner Profile
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Updated: 2026-04-24
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## Style
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- Learns best with: Analogies (Memory page <-> Capsule hotel), Concrete trade-offs (Latency vs Throughput)
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- Strength: Strong logical intuition regarding memory constraints.
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- Pace: Fast. Grasped PagedAttention/TP concepts quickly from first principles.
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## Patterns
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- Tends to focus on memory usage ("is it OOM?"), which is a good instinct for inference tuning.
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- Needs precision on API flags (e.g., `--tensor-parallel-size`).
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## Topics
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- vLLM Inference Optimization (10/10 concepts mastered, 2026-04-24)
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