Coerce ClassLabel.names to plain str to fix invalid YAML in README.md

[RudrenduPaul]

Coerce ClassLabel.names to plain str to fix invalid YAML in README.md

Fixes #6919

Problem

push_to_hub can fail with:

ValueError: Invalid metadata in README.md.
- Invalid YAML in README.md: unknown tag !<tag:yaml.org,2002:python/tuple> (50:11)

This happens whenever a ClassLabel's names list contains elements that
are not exactly str — most commonly numpy.str_, which shows up whenever
names is built from numpy.unique(...) or read out of a pandas column
(a very common pattern for NER/token-classification labels, exactly as
described in the issue).

Root cause

ClassLabel.__post_init__ already normalizes the internal _int2str
mapping with str(name), but it left the public names list untouched.
When the dataset card YAML metadata is generated
(Features._to_yaml_list -> yaml.dump), PyYAML's default Dumper
selects a representer by exact type match, not isinstance. Since
numpy.str_ is a subclass of str but not str itself, it falls
through to the generic object representer, which serializes it with
unsafe !!python/object/apply:numpy... tags (including base64-encoded
binary state). The resulting README.md is technically written, but it
can no longer be parsed back with the strict yaml.safe_load used to
validate dataset card metadata, hence the "unknown tag" error.

Fix

Coerce every element of ClassLabel.names to a plain str in
__post_init__, mirroring what already happens for _int2str. This
guarantees only native Python strings ever reach the YAML dumper,
regardless of where names originally came from.

Testing

• Added a regression test
  (test_class_label_names_are_coerced_to_str in
  tests/features/test_features.py) that builds a ClassLabel from
  numpy.str_ values, dumps its YAML representation, and asserts it
  round-trips through yaml.safe_load — this reproduces the exact
  failure from the issue and fails without the fix.
• Ran the full tests/features/test_features.py, tests/test_info.py,
  and tests/test_metadata_util.py suites locally: 226 passed, 3
  skipped, no regressions.
• Verified with a minimal repro matching the issue's steps (labels
  derived via numpy.unique, cast to
  Sequence(ClassLabel(names=list(labels))), then dumping the resulting
  DatasetInfo to YAML) — the dump now round-trips through
  yaml.safe_load cleanly instead of raising ConstructorError.

Scope

Only src/datasets/features/features.py (the fix) and
tests/features/test_features.py (the regression test) are touched. No
unrelated code or docs were changed.

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Note: this PR was prepared with AI assistance (Claude Code) under my
direction — I reviewed the root-cause analysis, the fix, and the test
before submitting.