LLM Models · Open Source
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Our Swallow-MX-8x7b-NVE-v0.1 model has undergone continuous pre-training from the Mixtral-8x7B-Instruct-v0.1, primarily with the addition of Japanese language data.
We introduce EXAONE Deep, which exhibits superior capabilities in various reasoning tasks including math and coding benchmarks, ranging from 2.4B to 32B parameters developed and released by LG AI Research. Evaluation results show that 1) EXAONE Deep 2.4B outperforms other models…
State-of-the-art bilingual open-sourced Math reasoning LLMs. A solver , prover , verifier , augmentor .
StepFun-Formalizer: Unlocking the Autoformalization Potential of LLMs through Knowledge-Reasoning Fusion
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]
Overview The model is the instruction-tuned version of rinna/nekomata-14b . It adopts the Alpaca input format.
SEA-LION is a collection of Large Language Models (LLMs) which has been pretrained and instruct-tuned for the Southeast Asia (SEA) region. The size of the models range from 3 billion to 7 billion parameters. This is the card for SEA-LION-v1-3B.
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State-of-the-art bilingual open-sourced Math reasoning LLMs. A solver , prover , verifier , augmentor .
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).
Notice: This model requires transformers =4.31.0 to work properly.
Authors : Yizhe Zhang, Navdeep Jaitly (Apple)