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mlabonne authored a paper 3 days ago

LFM2 Technical Report

mlabonne authored a paper 3 days ago

Zero-Overhead Introspection for Adaptive Test-Time Compute

MaxLSB published a dataset about 1 month ago

kurakurai/gpqa-fr

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mlabonne

authored 2 papers 3 days ago

LFM2 Technical Report

Paper • 2511.23404 • Published Nov 28, 2025 • 50

Zero-Overhead Introspection for Adaptive Test-Time Compute

Paper • 2512.01457 • Published Dec 1, 2025 • 1

mlabonne

posted an update 20 days ago

Post

4773

New family of 1B models just dropped!

> LiquidAI/LFM2.5-1.2B-Base: 10T → 28T tokens
> LiquidAI/LFM2.5-1.2B-Instruct: new large-scale multi-stage RL
> LiquidAI/LFM2.5-1.2B-JP: our most polite model
> LiquidAI/LFM2.5-VL-1.6B: multi-image multilingual
> LiquidAI/LFM2.5-Audio-1.5B: 8x times faster, no quality loss

Super proud of this release 🤗

3 replies

MaxLSB

published a dataset about 1 month ago

kurakurai/gpqa-fr

Viewer • Updated Sep 1, 2025 • 1.17k • 12

MaxLSB

authored a paper 3 months ago

Luth: Efficient French Specialization for Small Language Models and Cross-Lingual Transfer

Paper • 2510.05846 • Published Oct 7, 2025 • 3

GAD-cell

updated 2 datasets 4 months ago

kurakurai/scholar

Viewer • Updated Oct 12, 2025 • 60.6k • 44 • 6

kurakurai/luth-sft

Viewer • Updated Oct 12, 2025 • 571k • 86 • 11

GAD-cell

updated 5 models 4 months ago

GAD-cell

authored a paper 4 months ago

Luth: Efficient French Specialization for Small Language Models and Cross-Lingual Transfer

Paper • 2510.05846 • Published Oct 7, 2025 • 3

mlabonne

posted an update 4 months ago

Post

8306

LiquidAI/LFM2-8B-A1B just dropped!

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

1 reply

mlabonne

posted an update 4 months ago

Post

3783

⚛️ New drop of tiny task-specific models!

Want to do data extraction, translation, RAG, tool use, or math on a Raspberry Pi? We got you covered! ✅

These tiny models were fine-tuned to perform narrow tasks extremely well, making them competitive with much larger models.

You can deploy them today on-device or even on GPUs for big data operations!

LiquidAI/liquid-nanos-68b98d898414dd94d4d5f99a