view post Post 5421 LiquidAI open-sources a new generation of edge LLMs! π₯³Based on a new hybrid architecture, these 350M, 700M, and 1.2B models are both fast and performant, ideal for on-device deployment.I recommend fine-tuning them to power your next edge application. We already provide Colab notebooks to guide you. More to come soon!π Blog post: https://www.liquid.ai/blog/liquid-foundation-models-v2-our-second-series-of-generative-ai-modelsπ€ Models: LiquidAI/lfm2-686d721927015b2ad73eaa38 See translation 1 reply Β· π₯ 15 15 π 3 3 + Reply
Static Word Embeddings for Sentence Semantic Representation Paper β’ 2506.04624 β’ Published Jun 5 β’ 3
Distilling LLM Agent into Small Models with Retrieval and Code Tools Paper β’ 2505.17612 β’ Published May 23 β’ 81
view post Post 2619 Google released MedGemma on I/O'25 π google/medgemma-release-680aade845f90bec6a3f60c4> 4B and 27B instruction fine-tuned vision LMs and a 4B pre-trained vision LM for medicine > available with transformers from the get-go π€they also released a cool demo for scan reading β‘οΈ google/rad_explainuse with transformers β€΅οΈ See translation 1 reply Β· π₯ 5 5 π€ 1 1 + Reply
Fixing Data That Hurts Performance: Cascading LLMs to Relabel Hard Negatives for Robust Information Retrieval Paper β’ 2505.16967 β’ Published May 22 β’ 23
KRLabsOrg/lettucedect-210m-eurobert-fr-v1 Token Classification β’ 0.2B β’ Updated May 18 β’ 5 β’ 1
view article Article π₯¬ LettuceDetect Goes Multilingual: Fine-tuning EuroBERT on Synthetic Translations By adaamko and 1 other β’ May 19 β’ 9
view article Article Vision Language Models (Better, Faster, Stronger) By merve and 4 others β’ May 12 β’ 506
view article Article Train 400x faster Static Embedding Models with Sentence Transformers By tomaarsen β’ Jan 15 β’ 205