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Maxime Labonne

@maximelabonne • 33,807 subscribers

Head of Post-Training @liquidai 🤗 HF: https://t.co/2ECS7Gjhwb 📝 Blog: https://t.co/Dxjebt3GZW

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Background agents running your calendar locally with LFM2.5-2.6B. Inference is free, so you can burn >1M tokens/hr at no marginal cost.

Background agents running your calendar locally with LFM2.5-2.6B. Inference is free, so you can burn >1M tokens/hr at no marginal cost.

18,257 Aufrufe • vor 1 Monat

LFM2-Audio just dropped! It's a 1.5B model that understands and generates both text and audio Inference 10x faster + quality on par with models 10x larger Available today on Hugging Face and our playground 🥳

LFM2-Audio just dropped! It's a 1.5B model that understands and generates both text and audio Inference 10x faster + quality on par with models 10x larger Available today on Hugging Face and our playground 🥳

85,053 Aufrufe • vor 11 Monaten

Here's our new, tiniest model: LFM2.5-230M! 🥳 We went even smaller to power ultra-low latency use cases like e-commerce and robotics. Here's a demo of LFM2.5-230M running on a Unitree G1, decomposing user prompts into a sequence of tool calls. Available today on Hugging Face!

Here's our new, tiniest model: LFM2.5-230M! 🥳 We went even smaller to power ultra-low latency use cases like e-commerce and robotics. Here's a demo of LFM2.5-230M running on a Unitree G1, decomposing user prompts into a sequence of tool calls. Available today on Hugging Face!

25,366 Aufrufe • vor 2 Monaten

Just found the dLLM library to create Diffusion Language Models It's still early but it's insanely fun to experiment with diffusion (training, inference, eval) dLLM has the potential of becoming the main library for diffusion LLMs

Just found the dLLM library to create Diffusion Language Models It's still early but it's insanely fun to experiment with diffusion (training, inference, eval) dLLM has the potential of becoming the main library for diffusion LLMs

75,518 Aufrufe • vor 10 Monaten

New tiny VLM: LFM2.5-VL-450M > Supports bounding box prediction, object detection, and function calling > Improved multilingual capabilities across 9 languages > Enhanced instruction following for vision and text tasks

New tiny VLM: LFM2.5-VL-450M > Supports bounding box prediction, object detection, and function calling > Improved multilingual capabilities across 9 languages > Enhanced instruction following for vision and text tasks

32,242 Aufrufe • vor 5 Monaten

LFM2.5-ColBERT-350M is a surprisingly reliable smart tool selector. We gave it 151 tools, and it consistently surfaces the 5 most relevant ones based on the user prompt. This saves tokens and improves accuracy. Ideal for hmmmm agentic edge models? 👀

LFM2.5-ColBERT-350M is a surprisingly reliable smart tool selector. We gave it 151 tools, and it consistently surfaces the 5 most relevant ones based on the user prompt. This saves tokens and improves accuracy. Ideal for hmmmm agentic edge models? 👀

19,216 Aufrufe • vor 2 Monaten

LFM2-2.6B-Transcript AMD🤝Liquid AI > Private, on-device meeting summarization > Cloud-level quality > Faster processing, lower memory footprint > Runs across CPU, GPU, and NPU on AMD Ryzen AI PC Great showcase of what tiny models can achieve when fine-tuned

LFM2-2.6B-Transcript AMD🤝Liquid AI > Private, on-device meeting summarization > Cloud-level quality > Faster processing, lower memory footprint > Runs across CPU, GPU, and NPU on AMD Ryzen AI PC Great showcase of what tiny models can achieve when fine-tuned

28,034 Aufrufe • vor 8 Monaten

LFM2-VL support with GGUF and llama.cpp 🥳 You can now run these tiny, hyper-efficient VLMs on your watch! We released quantized checkpoints for LFM2-VL-450M and LFM2-VL-1.6B on Hugging Face

LFM2-VL support with GGUF and llama.cpp 🥳 You can now run these tiny, hyper-efficient VLMs on your watch! We released quantized checkpoints for LFM2-VL-450M and LFM2-VL-1.6B on Hugging Face

19,959 Aufrufe • vor 1 Jahr

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