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Hacker News • 52일 전
LFM2.5 26억 매개변수 모델 공개
IMP 8/10
핵심 요약
해커뉴스에 따르면, 26억 개의 매개변수(Parameters)를 가진 LFM2.5 모델이 자신보다 4배나 큰 대형 언어 모델(LLM)들과 맞먹는 경쟁력 있는 성능을 보여주었습니다. 이는 모델 크기를 키우지 않아도 연산 효율을 극대화하여 소형 모델로도 고성능을 낼 수 있다는 점에서 AI 실무자들에게 매우 중요한 의미를 갖습니다.
번역된 본문
원문 제목: LFM2.5 2.6B 모델, 4배 더 큰 모델들과 경쟁력 확보 소스: 해커뉴스(Hackernews)
본문: 제공된 원문 데이터에는 AI 모델의 뉴스 내용 대신, 모델의 채팅 템플릿(Chat Template)을 구성하기 위한 Jinja 코드와 시스템 프롬프트 설정값들이 포함되어 있습니다. 이는 주로 AI 모델이 사용자의 지시사항과 도구(Tools)를 인식하고 처리할 때 사용되는 백엔드 포맷팅 코드입니다. 따라서 실제 뉴스 기사 본문은 요약된 헤드라인을 제외하고는 확인할 수 없으며, 모델의 함수 호출(tool_call) 및 메시지 파싱을 위한 기술적 스크립트가 전부입니다.
원문 보기 (영어)
","eos_token":"<|im_end|>","pad_token":"<|pad|>","use_default_system_prompt":false},"chat_template_jinja":"{{- bos_token -}}\n{%- set preserve_thinking = preserve_thinking | default(false) -%}\n\n{%- macro format_arg_value(arg_value) -%}\n {%- if arg_value is string -%}\n {{- \"'\" + (arg_value | replace(\"\\\\\", \"\\\\\\\\\") | replace(\"'\", \"\\\\'\") | replace(\"\\n\", \"\\\\n\") | replace(\"\\r\", \"\\\\r\")) + \"'\" -}}\n {%- elif arg_value is mapping or arg_value is iterable -%}\n {{- arg_value | tojson -}}\n {%- else -%}\n {{- arg_value | string -}}\n {%- endif -%}\n{%- endmacro -%}\n\n{%- macro parse_content(content) -%}\n {%- if content is string -%}\n {{- content -}}\n {%- elif content is mapping -%}\n {{- content | tojson -}}\n {%- elif content is iterable -%}\n {%- set _ns = namespace(result=\"\") -%}\n {%- for item in content -%}\n {%- if item is string -%}\n {%- set _ns.result = _ns.result + item -%}\n {%- elif item is mapping and item.get(\"type\") == \"image\" -%}\n {%- set _ns.result = _ns.result + \"<image>\" -%}\n {%- elif item is mapping and item.get(\"type\") == \"text\" -%}\n {%- set _ns.result = _ns.result + ((item.get(\"text\") or \"\") | string) -%}\n {%- else -%}\n {%- set _ns.result = _ns.result + (item | tojson) -%}\n {%- endif -%}\n {%- endfor -%}\n {{- _ns.result -}}\n {%- endif -%}\n{%- endmacro -%}\n\n{%- macro render_tool_calls(tool_calls) -%}\n {%- set tool_calls_ns = namespace(tool_calls=[]) -%}\n {%- for tool_call in tool_calls -%}\n {%- set func = tool_call[\"function\"] if \"function\" in tool_call else tool_call -%}\n {%- set func_name = func[\"name\"] -%}\n {%- set func_args = func.get(\"arguments\") -%}\n {%- set args_ns = namespace(arg_strings=[]) -%}\n {%- if func_args is mapping -%}\n {%- for arg_name, arg_value in func_args.items() -%}\n {%- set args_ns.arg_strings = args_ns.arg_strings + [arg_name + \"=\" + format_arg_value(arg_value)] -%}\n {%- endfor -%}\n {%- elif func_args is string and (func_args | trim) not in [\"\", \"{}\", \"null\"] -%}\n {{- raise_exception(\"Tool call arguments must be a mapping, got a JSON-encoded string: parse arguments with json.loads() before applying the chat template\") -}}\n {%- endif -%}\n {%- set tool_calls_ns.tool_calls = tool_calls_ns.tool_calls + [func_name + \"(\" + (args_ns.arg_strings | join(\", \")) + \")\"] -%}\n {%- endfor -%}\n {{- \"<|tool_call_start|>[\" + (tool_calls_ns.tool_calls | join(\", \")) + \"]<|tool_call_end|>\" -}}\n{%- endmacro -%}\n\n{%- set ns = namespace(system_prompt=\"\", last_user_index=-1) -%}\n{%- if messages and messages[0][\"role\"] == \"system\" -%}\n {%- if messages[0].get(\"content\") -%}\n {%- set ns.system_prompt = parse_content(messages[0][\"content\"]) -%}\n {%- endif -%}\n {%- set messages = messages[1:] -%}\n{%- endif -%}\n{%- if tools -%}\n {%- set ns.system_prompt = ns.system_prompt + (\"\\n\" if ns.system_prompt else \"\") + \"List of tools: [\" -%}\n {%- for tool in tools -%}\n {%- if tool is not string -%}\n {%- set tool = tool | tojson -%}\n {%- endif -%}\n {%- set ns.system_prompt = ns.system_prompt + tool -%}\n {%- if not loop.last -%}\n {%- set ns.system_prompt = ns.system_prompt + \", \" -%}\n {%- endif -%}\n {%- endfor -%}\n {%- set ns.system_prompt = ns.system_prompt + \"]\" -%}\n{%- endif -%}\n{%- if ns.system_prompt -%}\n {{- \"<|im_start|>system\\n\" + ns.system_prompt + \"<|im_end|>\\n\" -}}\n{%- endif -%}\n{%- for message in messages -%}\n {%- if message[\"role\"] == \"user\" -%}\n {%- set ns.last_user_index = loop.index0 -%}\n {%- endif -%}\n{%- endfor -%}\n{%- for message in messages -%}\n {{- \"<|im_start|>\" + message.role + \"\\n\" -}}\n {%- if message.role == \"assistant\" -%}\n {%- generation -%}\n {%- set keep_thinking = preserve_thinking or loop.index0 > ns.last_user_index -%}\n {%- set thinking = message.thinking or message.reasoning or message.reasoning_content -%}\n {%- set thinking = thinking if thinking is string else \"\" -%}\n {%- if thinking and keep_thinking -%}\n {{- \"<think>\" + thinking + \"</think>\" -}}\n {%- endif -%}\n {%- set _cfm_tag = \"CONTINUE_FINAL_MESSAGE_TAG \" -%}\n {%- set _has_cfm = false -%}\n {%- set content = \"\" -%}\n {%- if message.get(\"content\") -%}\n {%- set content = parse_content(message.content) -%}\n {%- endif -%}\n {%- if not keep_thinking and \"</think>\" in content -%}\n {%- set content = content.split(\"</think>\")[-1] | trim -%}\n {%- endif -%}\n {%- if content.endswith(_cfm_tag) -%}\n {%- set _has_cfm = true -%}\n {%- set _trunc_len = (content | length) - (_cfm_tag | length) -%}\n {%- set content = content[:_trunc_len] -%}\n {%- endif -%}\n {{- content -}}\n {%- if message.tool_calls -%}\n {{- render_tool_calls(message.tool_calls) -}}\n {%- endif -%}\n {%- if _has_cfm -%}\n {{- _cfm_tag -}}\n {%- endif -%}\n {{- \"<|im_end|>\\n\" -}}\n {%- endgeneration -%}\n {%- else %}\n {%- if message.get(\"content\") -%}\n {{- parse_content(message[\"content\"]) -}}\n {%- endif -%}\n {{- \"<|im_end|>\\n\" -}}\n {%- endif %}\n{%- endfor -%}\n{%- if add_generation_prompt -%}\n {{- \"<|im_start|>assistant\\n<think>\" -}}\n{%- endif -%}\n"},"createdAt":"2026-07-28T22:14:32.000Z","discussionsDisabled":false,"discussionsSorting":"recently-created","downloads":89680,"downloadsAllTime":89680,"id":"LiquidAI/LFM2.5-2.6B","isLikedByUser":false,"availableInferenceProviders":[],"showHuggingChatEntry":false,"inference":"","lastModified":"2026-08-07T10:30:38.000Z","likes":498,"pipeline_tag":"text-generation","library_name":"transformers","librariesOther":[],"trackDownloads":true,"model-index":null,"evalResults":[{"dataset":{"id":"LiquidAI/ifstruct-v1.0","isBenchmark":true,"task_id":"ifstruct_v1"},"value":85.49,"source":{"url":"https://www.liquid.ai/blog/lfm2-5-2-6b","name":"Liquid AI — LFM2.5-2.6B blog","isExternal":true},"filename":".eval_results/ifstruct.yaml","verified":false,"pullRequest":8,"label":"Ifstruct V1"}],"private":false,"repoType":"model","gated":false,"tags":["transformers","safetensors","lfm2","text-generation","liquid","lfm2.5","edge","conversational","ar","zh","en","fr","de","hi","id","it","ja","ko","pl","pt","ru","es","th","vi","arxiv:2511.23404","base_model:LiquidAI/LFM2.5-2.6B-Base","base_model:finetune:LiquidAI/LFM2.5-2.6B-Base","license:other","eval-results","endpoints_compatible","region:us"],"tag_objs":[{"id":"text-generation","label":"Text Generation","type":"pipeline_tag","subType":"nlp"},{"id":"transformers","label":"Transformers","type":"library"},{"id":"safetensors","label":"Safetensors","type":"library"},{"id":"ar","label":"Arabic","type":"language"},{"id":"zh","label":"Chinese","type":"language"},{"id":"en","label":"English","type":"language"},{"id":"fr","label":"French","type":"language"},{"id":"de","label":"German","type":"language"},{"id":"hi","label":"Hindi","type":"language"},{"id":"id","label":"Indonesian","type":"language"},{"id":"it","label":"Italian","type":"language"},{"id":"ja","label":"Japanese","type":"language"},{"id":"ko","label":"Korean","type":"language"},{"id":"pl","label":"Polish","type":"language"},{"id":"pt","label":"Portuguese","type":"language"},{"id":"ru","label":"Russian","type":"language"},{"id":"es","label":"Spanish","type":"language"},{"id":"th","label":"Thai","type":"language"},{"id":"vi","label":"Vietnamese","type":"language"},{"id":"lfm2","label":"lfm2","type":"other","clickable":true},{"id":"liquid","label":"liquid","type":"other","clickable":true},{"id":"lfm2.5","label":"lfm2.5","type":"other","clickable":true},{"id":"edge","label":"edge","type":"other","clickable":true},{"id":"conversational","label":"conversational","type":"other","clickable":true},{"id":"base_model:LiquidAI/LFM2.5-2.6B-Base","label":"base_model:LiquidAI/LFM2.5-2.6B-Base","type":"other","clickable":true},{"id":"base_model:finetune:LiquidAI/LFM2.5-2.6B-Base","label":"base_model:finetune:LiquidAI/LFM2.5-2.6B-Base","type":"other","clickable":true},{"id":"eval-results","label":"Eval Results","type":"other","clickable":true},{"id":"endpoints_compatibl