Maxime Labonne's banner

Maxime Labonne

@maximelabonne • 29,646 subscribers

Head of Post-Training @liquidai 💻 GitHub: https://t.co/ElXDsjzGOn 🤗 HF: https://t.co/2ECS7Gjhwb 📝 Blog: https://t.co/Gz5bhbYuIy

Videos

Anya Rossi

sweetdream.ai

SweetDream.ai•Sponsored•Livecam

Watch Anya Live

Anya is streaming live right now! Join her private show and enjoy exclusive content.

Exclusive private shows

1.2k viewers online

Private Show

Join now for exclusive access

Free preview available • Premium content

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!

25,058 次观看 • 1 个月前

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? 👀

19,185 次观看 • 1 个月前

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 🥳

84,952 次观看 • 9 个月前

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

75,477 次观看 • 8 个月前

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

32,173 次观看 • 3 个月前

LFM2-8B-A1B just dropped on Hugging Face! 8.3B params with only 1.5B active/token 🚀 > Quality ≈ 3–4B dense, yet faster than Qwen3-1.7B > MoE designed to run on phones/laptops (llama.cpp / vLLM) > Pre-trained on 12T tokens → strong math/code/IF

LFM2-8B-A1B just dropped on Hugging Face! 8.3B params with only 1.5B active/token 🚀 > Quality ≈ 3–4B dense, yet faster than Qwen3-1.7B > MoE designed to run on phones/laptops (llama.cpp / vLLM) > Pre-trained on 12T tokens → strong math/code/IF

40,714 次观看 • 9 个月前

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

27,703 次观看 • 6 个月前

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

19,947 次观看 • 11 个月前

没有更多内容可加载