Update documentation to use mask utility in examples

[LoserCheems]

Linked #195
Replace manual mask construction with a utility-based approach in both English and Chinese documentation to simplify examples and ensure consistency with the current API.

[Copilot]

Pull Request Overview

This PR updates the documentation to use the create_mask utility function instead of manual mask construction in both English and Chinese README files. The changes simplify the examples and promote consistency with the current API design.

Key changes:

• Import and utilize the create_mask utility function from flash_dmattn.utils.mask
• Replace manual top-k mask generation logic with a single utility function call
• Standardize variable naming from attention_mask/attention_bias to attn_mask/attn_bias

Reviewed Changes

Copilot reviewed 2 out of 2 changed files in this pull request and generated 2 comments.

File	Description
README.md	Updated English documentation to use the mask utility and simplified variable names
README_zh.md	Updated Chinese documentation with the same utility-based approach and variable naming

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[Copilot]

The comment on line 171 says 'Create bias for sparse attention' but the code creates attn_mask, not attn_bias. Additionally, attn_bias is used on line 177 but never defined. The line should create attn_bias instead of attn_mask, and the subsequent create_mask call should initialize attn_mask from None or an appropriate default.

Suggested change

	attn_mask = torch.ones(batch_size, num_kv_heads, seq_len, seq_len, device=device, dtype=dtype)
	attn_bias = torch.ones(batch_size, num_kv_heads, seq_len, seq_len, device=device, dtype=dtype)
	attn_mask = None

[Copilot]

The variable attn_mask is passed to create_mask on line 178 but is never defined before this usage. Either initialize attn_mask before the conditional block or pass None if the utility function supports it.

[Copilot]

Pull Request Overview

Copilot reviewed 2 out of 2 changed files in this pull request and generated no new comments.

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