{"schema_version":"onlylabs.public_signal.v1","title":"OpenBMB (MiniCPM) Writing: BMTrain, an efficient toolkit for big model training, can save up to 90% of training costs","description":"OpenBMB (MiniCPM) writing signal with public source context, captured evidence pages, related signals, and category-scoped analysis context.","url":"https://onlylabs.fyi/signals/095cc9b3-8122-4ae9-953e-2d9a426ab070","json_url":"https://onlylabs.fyi/signals/095cc9b3-8122-4ae9-953e-2d9a426ab070/signal.json","generated_at":"2026-06-08T15:46:45.389+00:00","org":{"slug":"openbmb","name":"OpenBMB (MiniCPM)","category":"neolab","category_label":"Neolab","dossier_url":"https://onlylabs.fyi/labs/openbmb","dossier_json_url":"https://onlylabs.fyi/labs/openbmb/dossier.json"},"related_urls":{"signal":"https://onlylabs.fyi/signals/095cc9b3-8122-4ae9-953e-2d9a426ab070","signal_json":"https://onlylabs.fyi/signals/095cc9b3-8122-4ae9-953e-2d9a426ab070/signal.json","source":"https://medium.com/@openbmb/bmtrain-an-efficient-toolkit-for-big-model-training-can-save-up-to-90-of-training-costs-abc741bf0d56?source=rss-4a6e3e4a369a------2","lab_dossier":"https://onlylabs.fyi/labs/openbmb","lab_dossier_json":"https://onlylabs.fyi/labs/openbmb/dossier.json","analysis":"https://onlylabs.fyi/analysis/openbmb","analysis_json":"https://onlylabs.fyi/analysis/openbmb/analysis.json","analysis_evidence_json":"https://onlylabs.fyi/analysis/openbmb/evidence.json","category":"https://onlylabs.fyi/neolabs","category_json":"https://onlylabs.fyi/neolabs.json","category_feed":"https://onlylabs.fyi/neolabs/feed.xml","category_signals_json":"https://onlylabs.fyi/signals.json?category=neolab","topic":"https://onlylabs.fyi/topics/talking","topic_signals_json":"https://onlylabs.fyi/topics/talking/signals.json?category=neolab","topic_feed":"https://onlylabs.fyi/topics/talking/feed.xml?category=neolab","data_business":null},"answer_pack":{"answer":"OpenBMB (MiniCPM) published BMTrain, an efficient toolkit for big model training, can save up to 90% of training costs. 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Research shows that increasing the parameters and data scale is an effective way to further improve the performance of language models. The exploration of big models of one billion, ten billion , or even one hundred billion has become a hot topic in the industry, which triggers fierce competition between global research institutions and Internet enterprises, pushing the scale and performance of big model to a new height. In addition to well-known institutions such as Google and OpenAI, relevant Chinese research institutions and companies have also emerged in recent years, booming the research and application of big models. Thus, artificial intelligence has entered the “era of big models”. 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Research shows that increasing the parameters and data scale is an effective way to further improve the performance of language models. The exploration of big models of one billion, ten billion , or even one hundred billion has become a hot topic in the industry, which triggers fierce competition between global research institutions and Internet enterprises, pushing the scale and performance of big model to a new height. In addition to well-known institutions such as Google and OpenAI, relevant Chinese research institutions and companies have also emerged in recent years, booming the research and application of big models. Thus, artificial intelligence has entered the “era of big models”. 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