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Accelerating vision-language models with LFM2.5-VL-DSpark
How does speculative decoding work for VLMs The vision drafter uses the same architecture as our text LFM2.5-DSpark drafters: it captures the target model's hidden states at a fixed set of tapped layers and conditions on them to draft a block of k candidate tokens. Image patches and text tokens are projected into a sh…
Hugging Face
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This issue is for keeping track of the recurrent Whisper asks as well as the linked on-going efforts to support that feature, if any. When a feature request has no linked PR, feel free to claim the work here if you want to help! - Related issues: https://github.com/vllm-project/vllm/issues/19556, https://github.com/vl…
vllm-project/vllmAbout 4 hr语音推理部署
Cross-checked · GitHub Good First Issues · aiVerified Sep 25, 2026Add to path
These enhancements are to have a better UX when using foreach_map, suggested in a few places, but most recently, https://github.com/pytorch/pytorch/issues/158371#issuecomment-3088757068 These enhancements should allow easier compiler-first custom optimizer implementations. cc @chauhang @penguinwu @voznesenskym @EikanW…
pytorch/pytorchAbout 4 hr编译器性能优化
Cross-checked · GitHub Good First Issues · aiConfirmed still open · Sep 25, 2026Add to path
Defenders wanting to use advanced AI have faced a difficult dilemma: adopt enormous frontier models that could be expensive to deploy and difficult to control across enterprise codebases, or turn to smaller open-weight models that might struggle with complex vulnerability remediation and require teams to build their o…
Google DeepMindPublished Sep 3, 2026
Official source · Google DeepMind BlogVerified Sep 25, 2026
Today, we’re introducing two new models that bring advancements in near real-time reasoning to more effectively enable voice agents and make conversing with AI feel more intuitive and intelligent.
Google DeepMindPublished Sep 16, 2026
Official source · Google DeepMind BlogVerified Sep 25, 2026