Unverified50% confidenceFactExact time
MemT-1.0's training pipeline uses 34B tokens of training data.
1
Sources
50%
Confidence
Medium-term (~90 days)
Relevance
10/20/2026
First Seen
Valid until: 1/18/2027
Sources
Related Entities
Related Claims
UnverifiedMemT-1.0 adopts a two-stage training pipeline: continued pre-training plus post-training.71% similarUnverifiedTraining used a context length of 256 and a micro-batch size of 16 with gradient accumulation, and peak memory during the main training process was 1.54 GiB65% similarUnverifiedEach RL training step of MiMo V2.6 processes approximately 2B tokens, using 1,568 prompts with 16 rollouts per prompt.62% similarUnverifiedIn a classification task with nearly a thousand points, using a batch size of 30 can speed up training by approximately 33 times.58% similarUnverified在大模型训练中，通信开销往往占到总训练时间的30%以上58% similar
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