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@vquy897023p: #disturbing #encounter #caughtoncamera #scarystories #videoviral

Connie Keebler
Connie Keebler
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Friday 12 June 2026 11:18:03 GMT
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#ardventcalendar #giftforhim #tiktokmademebuyit #tiktokshopcreatorpicks #tiktokfalldealsforyou
#ardventcalendar #giftforhim #tiktokmademebuyit #tiktokshopcreatorpicks #tiktokfalldealsforyou
AWS's Strands Labs just open-sourced Strands Decider 2B, and it's a different kind of model. It doesn't write text. You give it some text, a question and a list of options, and it picks one, answers yes or no, or scores on a scale, with a confidence on every answer. It can never answer outside your list. Under the hood it's Qwen3.5-2B-Base with the language-model head removed and a pointer head of about a million parameters in its place. 1.9B parameters in total, one forward pass, no decoding loop. On JevBench's public set it gets 72.3% (167 of 231 tasks), 3rd of 33 models in the 2B class, and 100% of the easy tasks. The two models above it are inside the retrain noise the team itself flags, and overall it ranks 50th of 89, behind much bigger reasoning models. Speed is the point: a median 115 ms per question on an RTX 3090 and 153 ms on an M3 Pro Mac, in the team's own tests. On short tasks it had never seen, answers at 0.9 confidence or more were right about 95% of the time. Where I'd use it: tool selection, model routing, triage, guardrails and cheap evals inside an agent. Where I wouldn't: coding, chat or summaries. It can't do them. It's Apache 2.0, with the weights on Hugging Face and all the training data and scripts on GitHub. The full recipe retrains in about 11 hours on one RTX 3090. No hosted AWS API was announced. Sources: strandsagents.com/blog/introducing-strands-decider and github.com/strands-labs/strands-decider Independent briefing by CodenamePoshan, not a Strands or AWS post. #AWS #AIAgents #OpenSource #MachineLearning #AIEngineering #DeveloperTools
AWS's Strands Labs just open-sourced Strands Decider 2B, and it's a different kind of model. It doesn't write text. You give it some text, a question and a list of options, and it picks one, answers yes or no, or scores on a scale, with a confidence on every answer. It can never answer outside your list. Under the hood it's Qwen3.5-2B-Base with the language-model head removed and a pointer head of about a million parameters in its place. 1.9B parameters in total, one forward pass, no decoding loop. On JevBench's public set it gets 72.3% (167 of 231 tasks), 3rd of 33 models in the 2B class, and 100% of the easy tasks. The two models above it are inside the retrain noise the team itself flags, and overall it ranks 50th of 89, behind much bigger reasoning models. Speed is the point: a median 115 ms per question on an RTX 3090 and 153 ms on an M3 Pro Mac, in the team's own tests. On short tasks it had never seen, answers at 0.9 confidence or more were right about 95% of the time. Where I'd use it: tool selection, model routing, triage, guardrails and cheap evals inside an agent. Where I wouldn't: coding, chat or summaries. It can't do them. It's Apache 2.0, with the weights on Hugging Face and all the training data and scripts on GitHub. The full recipe retrains in about 11 hours on one RTX 3090. No hosted AWS API was announced. Sources: strandsagents.com/blog/introducing-strands-decider and github.com/strands-labs/strands-decider Independent briefing by CodenamePoshan, not a Strands or AWS post. #AWS #AIAgents #OpenSource #MachineLearning #AIEngineering #DeveloperTools
RUDE!!
RUDE!!
Kệ phơi giầy dép 3 tầng xoay 360 độ, chất liệu thép không gỉ siêu tiện lợi #kệphơigiàydép #giadụngtiệních24h #thinhhanh #xuhuong #dogiadung
Kệ phơi giầy dép 3 tầng xoay 360 độ, chất liệu thép không gỉ siêu tiện lợi #kệphơigiàydép #giadụngtiệních24h #thinhhanh #xuhuong #dogiadung
#WHITENOWAffiliateCompetition @Closeup Indonesia
#WHITENOWAffiliateCompetition @Closeup Indonesia
first place when i land #fyp #timessquare #newyorkcity #america #trip
first place when i land #fyp #timessquare #newyorkcity #america #trip

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