docs: 重构 README 结构,全文档添加目录导航

- README 新增 Getting Started 端到端流程,整合快速开始与演示,去重精简
- 中文 README 同步英文版结构,预处理配置改用 seq 策略
- inference.md 补充 SSE 流式格式、错误响应、/stats 端点文档
- params.md 扩展为 CLI 参考,覆盖 server/generate/preprocess 参数表
- dataflow.md 拆分 tokenization/format detection/backend 子节,新增流程图
- architecture/training/inference/preprocessing 均添加目录导航
- 移除 README CI badge
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# Training
## Contents
- [Autoregression](#autoregression)
- [Causal Mask](#causal-mask)
- [Rotary Position Embedding (RoPE)](#rotary-position-embedding-rope)
- [Training Loop](#training-loop)
- [Strategies](#strategies) — SEQ, SFT, DPO, GRPO
- [LR Schedulers](#lr-schedulers)
- [Gradient Checkpointing](#gradient-checkpointing)
- [Checkpoint](#checkpoint)
- [TrainContextBuilder](#traincontextbuilder-builder-pattern)
- [Training CLI](#training-cli)
### Autoregression
Given a token sequence, the model predicts the probability of the next token. Each generated token is appended to the input and fed back, repeating until an end-of-sequence token or max length.