Add Muse Glimmer chat template

[qgallouedec]

Stacked on add-muse-glimmer.

• Vendored muse_glimmer.jinja (as shipped by meta-models/Muse-Glimmer-30B) and muse_glimmer_training.jinja, registered in get_training_chat_template.
• The training variant wraps the whole assistant branch — every ATEM channel of the turn — in {% generation %} / {% endgeneration %}, same treatment as gptoss_training.jinja, which shares the <|start|>assistant cue and one-block-per-channel layout. Rendering is byte-identical to the original.
• No add_response_schema entry: the checkpoint ships its own response_template, which TRL already leaves alone.
• Tests: added to the tool-calling, training-template and parse-response lists in test_chat_template_utils.py. test_parse_response_tool_call_with_content gets a Muse Glimmer branch next to the existing GPT-OSS one — a turn with tool calls has no to=user channel, so text alongside a tool call belongs in the to=self channel.
• pytest tests/test_chat_template_utils.py -k muse_glimmer: 21 passed, 1 skipped.

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Note

Low Risk
Additive templates, registry wiring, and tests only; no changes to training loops or auth/data paths.

Overview
Adds Muse Glimmer as a supported chat-template family so TRL can recognize the model and swap in a training template for SFT/GRPO.

Vendored muse_glimmer.jinja (ATEM: to=self reasoning, per-tool channels with <atem:function_calls>, to=user content, multimodal placeholders) and muse_glimmer_training.jinja, which wraps the full assistant turn—all ATEM channels—in {% generation %} / {% endgeneration %} (same pattern as GPT-OSS). get_training_chat_template maps the reference template to the training variant; docs list Muse Glimmer among supported families.

Tests cover tool calling, training-template behavior, and response parsing (including reasoning_content alongside tool calls, since tool turns have no to=user channel). No add_response_schema hook—the checkpoint already ships response_template.

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[bot-ci-comment]

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