Jimmy Smith
@jimmysmith1919
318 Following 629 Followers
Try out our new Q4_0 checkpoints for the LFM2.5 series trained with QAD. They recover a fair amount of quality lost to standard quantization techniques.
230M:
350M:
1.2B:
2.6B:
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Today we are releasing LFM2.5-2.6B, a very strong on-device agentic model.
We continued pre-training to 34T tokens, expanded the vocab (as in and utilized a 4-stage post-training pipeline to unlock the strong agentic capabilities for its size.
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