Fix minibatch splitting in char-RNN classification tutorial

[ability-spec]

The char-RNN classification tutorial uses floor division to calculate the number of minibatches. With fewer examples than n_batch_size, training crashes with:
ValueError: number sections must be larger than 0.

Non-divisible datasets can also produce batches larger than requested.

This change uses ceiling division, preserving balanced batches while supporting small nonempty datasets and respecting the requested batch size.

Validation

• CPU boundary checks: original 3/9 passed; patched 9/9 passed.
• Complete tutorial script finished 27 epochs and evaluation on a small synthetic names dataset.
• Repository lintrunner and git diff --check passed.
• Full documentation build and original dataset training were not run.

Checklist

• Only one issue is addressed in this pull request.
• No unrelated changes are included.

[pytorch-bot]

🔗 Helpful Links

🧪 See artifacts and rendered test results at hud.pytorch.org/pr/pytorch/tutorials/3975

• 📄 Preview Python docs built from this PR

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