47 lines
1.9 KiB
Python
47 lines
1.9 KiB
Python
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"""
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HYV3 chat template registration for LLaMA Factory.
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Usage:
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1. Copy this file's register_template block into LLaMA Factory's
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src/llamafactory/data/template.py (for upstream MR).
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2. Or import this module before training to register at runtime:
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import hy_v3_template
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"""
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from llamafactory.data.template import ReasoningTemplate, register_template
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from llamafactory.data.formatter import EmptyFormatter, StringFormatter
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# ---------------------------------------------------------------------------
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# HYV3 (MoE, pure text) chat template
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#
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# Token format (from chat_template.jinja & tokenizer_config.json):
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# BOS: <｜hy_begin▁of▁sentence｜>
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# System: {system_content} (directly after BOS, no role tag)
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# User: <｜hy_User｜>{user_content}
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# Assistant: <｜hy_Assistant｜>{assistant_content}<｜hy_eos｜>
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# EOS: <｜hy_eos｜>
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#
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# Loss mask: only compute loss on assistant content (including <｜hy_eos｜>).
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#
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# Note: The system message has NO explicit role token -- it is placed right
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# after BOS. The eos_token is <｜hy_eos｜>.
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#
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# Reasoning: Supports think tags via ReasoningTemplate.
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# - thought_words: ("<think>", "</think>") matching jinja template
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# - enable_thinking: set globally via data_args.enable_thinking (default True)
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# - Training data always includes think tags (empty or with content)
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# ---------------------------------------------------------------------------
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register_template(
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name="hy_v3",
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template_class=ReasoningTemplate,
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format_user=StringFormatter(slots=["<｜hy_User｜>{{content}}"]),
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format_assistant=StringFormatter(slots=["<｜hy_Assistant｜>{{content}}", {"eos_token"}]),
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format_system=StringFormatter(slots=["{{content}}"]),
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format_prefix=EmptyFormatter(slots=[{"bos_token"}]),
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thought_words=("<think>", "</think>"),
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stop_words=["<｜hy_eos｜>"],
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efficient_eos=True,
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)
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