LLM Models
Browse the world's large language models. Compare parameters, benchmarks, VRAM and more.
🤗 Hugging Face 💻 Github Repository 📑 Technique Report 💬 Issues & Discussions
This model is a version of bigscience/bloomz post-processed to be run at home using the Petals swarm.
SEA-Safeguard is a collection of safety-focused Large Language Models (LLMs) built upon the SEA-LION family, designed specifically for the Southeast Asia (SEA) region.
SEA-LION is a collection of Large Language Models (LLMs) which have been pretrained and instruct-tuned for the Southeast Asia (SEA) region.
WARNING: This is an intermediary checkpoint and WIP project. It is not fully trained yet. You might want to use Bloom-1B3 if you want a model that has completed training. This model is a distilled version of Bloom-1B3 (10x distillation)
Coherence Modelling You can test the model at coherence modeling. If you want to find out more information, please contact us at sg-nlp@aisingapore.org.
SEA-LION is a collection of Large Language Models (LLMs) which has been pretrained and instruct-tuned for the Southeast Asia (SEA) region. The sizes of the models range from 3 billion to 7 billion parameters.
🤗 Hugging Face 💻 Github Repository 📑 Technique Report 💬 Issues & Discussions
WARNING: This is an intermediary checkpoint and WIP project. It is not fully trained yet. You might want to use Bloom-1B3 if you want a model that has completed training. This model is a distilled version of Bloom-1B3
[!NOTE] Note: " -Paddle " models use PaddlePaddle weights, while " -PT " models use Transformer-style PyTorch weights.