LLM Models

Llama-SEA-LION-v3-70B SEA-LION is a collection of Large Language Models (LLMs) which have been pretrained and instruct-tuned for the Southeast Asia (SEA) region.

1. Model Summary 2. Use 3. Limitations 4. Training 5. Evaluation 7. Citation

AquilaMoE: Efficient Training for MoE Models with Scale-Up and Scale-Out Strategies Language Foundation Model & Software Team Beijing Academy of Artificial Intelligence (BAAI) [Paper(released soon)] [Code] [github]

[!NOTE] Note: " -Paddle " models use PaddlePaddle weights, while " -PT " models use Transformer-style PyTorch weights.

💻Github Repo • 🤗Model Collections • 📜Technical Report

Aquila is a large language model independently developed by BAAI. Building upon the Aquila model, we continued pre-training, SFT (Supervised Fine-Tuning), and RL (Reinforcement Learning) through a multi-stage training process, ultimately resulting in the AquilaMed-RL model. This…

📖 Paper 🏠 Github 🤗 Spatial-SSRL-7B Model 🤗 Spatial-SSRL-3B Model 🤗 Spatial-SSRL-Qwen3VL-4B Model 🤗 Spatial-SSRL-81k Dataset 📰 Daily Paper

Llama 3 Youko 8B (rinna/llama-3-youko-8b)

[!NOTE] Note: " -Paddle " models use PaddlePaddle weights, while " -PT " models use Transformer-style PyTorch weights.

This is a 3B-parameter decoder-only Japanese language model fine-tuned on instruction-following datasets, built on top of the base model Japanese StableLM-3B-4E1T Base.

[!NOTE] Note: " -Paddle " models use PaddlePaddle weights, while " -PT " models use Transformer-style PyTorch weights.

A cute robot wearing a kimono writes calligraphy with one single brush — Stable Diffusion XL