
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

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!
Maxime Labonne25,058 просмотров • 1 месяц назад

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
Maxime Labonne40,714 просмотров • 9 месяцев назад

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
Maxime Labonne27,703 просмотров • 6 месяцев назад
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