LLM Models · Open Source
Browse the world's large language models. Compare parameters, benchmarks, VRAM and more.
AHN: Artificial Hippocampus Networks for Efficient Long-Context Modeling
Our Swallow model has undergone continual pre-training from the Llama 2 family, primarily with the addition of Japanese language data. The tuned versions use supervised fine-tuning (SFT). Links to other models can be found in the index.
Model Summary Chat with the model at: https://huggingface.co/spaces/HuggingFaceTB/instant-smol
AHN: Artificial Hippocampus Networks for Efficient Long-Context Modeling
[!NOTE] Note: " -Paddle " models use PaddlePaddle weights, while " -PT " models use Transformer-style PyTorch weights.
AHN: Artificial Hippocampus Networks for Efficient Long-Context Modeling
We introduce an updated version of LongCat-Flash-Thinking-2601, a powerful and efficient Large Reasoning Model (LRM) with 560 billion total parameters, built upon an innovative Mixture-of-Experts (MoE) architecture. Beyond inheriting the domain-parallel training recipe in our pre…
SEA-LION is a collection of Large Language Models (LLMs) which have been pretrained and instruct-tuned for the Southeast Asian (SEA) region. Nemotron-SEA-LION-v4.8-30B-A3B is built upon the aisingapore/Nemotron-SEA-LION-v4.8-30B-A3B-Base, by fine-tuning with a mixture of SFT and…
Overview The model is the instruction-tuned version of rinna/youri-7b . It adopts a chat-style input format.
🦉GitHub 💬WeChat 百川API支持搜索增强和192K长窗口，新增百川搜索增强知识库、限时免费！ 🚀 百川大模型在线对话平台 已正式向公众开放 🎉
Our Swallow model has undergone continual pre-training from the Llama 2 family, primarily with the addition of Japanese language data. The tuned versions use supervised fine-tuning (SFT). Links to other models can be found in the index.