# Lightweight and efficient

A static quantized version of the Google Gemma-3n-E2B model, offering various quantization types to balance model size and performance.

Gemma 3n is a lightweight and state-of-the-art open-source multimodal model family launched by Google, built on the same research and technology as the Gemini model. It supports text, audio, and visual inputs and is suitable for various tasks.

Gemma 3n is a lightweight and state-of-the-art open-source multimodal model family launched by Google. It is built on the same research and technology as the Gemini model and supports text, audio, and visual inputs.

This is a statically quantized version of the mshojaei77/gemma-3-4b-persian-v0 model, specifically optimized for Persian text generation tasks.

Depth Anything V2 is currently the most powerful monocular depth estimation model, trained on 595,000 synthetically annotated images and over 62 million real unlabeled images, offering finer details and stronger robustness.

Qwen2 1.5B is a compact language model specifically optimized for Italian, with performance close to ITALIA (iGenius) but 6 times smaller in size.

Named entity recognition model for Danish, Norwegian, Swedish, Icelandic, and Faroese, fine-tuned based on NbAiLab/nb-bert-base