LLM Models
Browse the world's large language models. Compare parameters, benchmarks, VRAM and more.
Overview We conduct continual pre-training of qwen-7b on 30B tokens from a mixture of Japanese and English datasets. The continual pre-training significantly improves the model's performance on Japanese tasks. It also enjoys the following great features provided by the original Q…
State-of-the-art bilingual open-sourced Math reasoning LLMs. A solver , prover , verifier , augmentor .
This model is an example of the Simple Self-Distillation (SimpleSD) method that improves code generation by fine-tuning a language model on its own sampled outputs—without rewards, verifiers, teacher models, or reinforcement learning. Please see the paper below for more informati…
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).
A 15B-parameter token-mixer supernet with 8 optimized deployment presets spanning 1.0× to 10.7× decode throughput at 32K sequence length, all from a single checkpoint. Derived from Apriel-1.6 through stochastic distillation and targeted supervised fine-tuning.
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.
StepFun-Prover-Preview-32B is a theorem proving model developed by StepFun Team. It can iteratively refine the proof sketch via interacting with Lean4, and achieve 70.0% accuracy with Pass@1 on MiniF2F-test. Advanced usage examples can be seen in github.
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StepFun-Prover-Preview-7B is a theorem proving model developed by StepFun Team. It can iteratively refine the proof sketch via interacting with Lean4, and achieve 66.0% accuracy with Pass@1 on MiniF2F-test. Advanced usage examples can be seen in github.
python from transformers import pipeline
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.
State-of-the-art bilingual open-sourced Math reasoning LLMs. A solver , prover , verifier , augmentor .