LLM Models

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

Llama3 Swallow - Built with Meta Llama 3

- Model creator: AI Singapore - Original model: Qwen-SEA-LION-v4-32B-IT

WARNING: The checkpoints on this repo are not fully trained model. Evaluations of intermediary checkpoints and the final model will be added when conducted (see below).

SEA-Guard is a collection of safety-focused Large Language Models (LLMs) built upon the SEA-LION family, designed specifically for the Southeast Asia (SEA) region.

Gemma-2-Llama-Swallow series was built by continual pre-training on the gemma-2 models. Gemma 2 Swallow enhanced the Japanese language capabilities of the original Gemma 2 while retaining the English language capabilities. We use approximately 200 billion tokens that were sampled…

Cola DLM ( Co ntinuous La tent D iffusion L anguage M odel) is a hierarchical continuous latent-space diffusion language model. It combines a Text VAE with a block-causal Diffusion Transformer (DiT) prior: the VAE maps text into continuous latent sequences and decodes latents bac…

InternLM2.5-Step-Prover is a 7B language model which achieves state-of-the-art performances on MiniF2F, ProofNet, and Putnam math benchmarks, showing its formal math proving ability in multiple domains.

- 2023/08/02 We uploaded the newly trained rinna/bilingual-gpt-neox-4b-instruction-sft with the MIT license. - Please refrain from using the previous model released on 2023/07/31 for commercial purposes if you have already downloaded it. - The new model released on 2023/08/02 is…

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.

WARNING: The checkpoints on this repo are not fully trained model. Evaluations of intermediary checkpoints and the final model will be added when conducted (see below).