chore(deps): bump renderers (tokenizer config-build fallback for Laguna)

[hallerite]

Bumps the deps/renderers submodule from 2ec28a8 → 89ab3f0, pulling in renderers#72.

Why

Loading a tokenizer for the Laguna model series (poolside/Laguna-XS.2) crashed renderers with:

KeyError: "Missing required keys in `rope_parameters` for 'rope_type'='default': {'rope_theta'}"

AutoTokenizer.from_pretrained always builds the model config first (to resolve the tokenizer class), even for a plain fast tokenizer. Building Laguna's config runs HF's RoPE validator, which rejects its nested rope_parameters (full_attention/sliding_attention, no top-level rope_theta) when constructed outside vLLM's patch_rope_parameters. The KeyError escaped and killed the tokenizer load — a modeling-layer concern breaking something the tokenizer never needed.

What changed in renderers#72

When AutoTokenizer fails building the config, fall back to loading the repo's self-contained tokenizer.json directly via PreTrainedTokenizerFast (no model config, no RoPE). Modeling-agnostic, runs under the fastokens patch (Laguna keeps the Rust speedup), excludes custom auto_map tokenizers, and re-raises the original error otherwise.

With this bump, Laguna runs no longer need --no-renderers as a workaround.

🤖 Generated with Claude Code

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Note

Low Risk
Dependency and lockfile updates with a localized tokenizer-load fallback; no auth, data, or core training-path changes in this diff.

Overview
Updates deps/renderers (renderers#72) so tokenizer loading no longer dies on Laguna-style models when Hugging Face config build hits RoPE validation (rope_theta / nested rope_parameters). Renderers now falls back to tokenizer.json via PreTrainedTokenizerFast when AutoTokenizer fails on config, so Laguna runs can use renderers without --no-renderers.

The visible diff refreshes uv.lock: advances exclude-newer, and relaxes the verifiers dev metadata constraint on openai-harmony from >=0.0.8 to >=0.0.4 (likely from re-locking after the bump).

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