bidirectional attention mask
AssessTechniques
An attention pattern that lets each token attend to tokens on both sides, not only previous ones.
Why it's here
Placed in Assess: 1 article(s) of evidence from 1 source(s), led by model releases, with 1 in the last 30 days. Confidence 24%. Low accumulated evidence, so it defaults conservatively pending more signal.
Evidence (1)
- 7Hugging Face Blog·7/28/2026model_releaseLiquidAI releases LFM2.5 encoders for fast long-context CPU inference
Hugging Face announced two new encoder models, LFM2.5-Encoder-230M and LFM2.5-Encoder-350M, designed for long-context inference with strong accuracy and low latency on CPU. The models support up to 8,192 tokens, are trained with masked language modeling, and are positioned for use cases such as classification, intent routing, safety filtering, and PII detection.