LLM Models · Open Source
Browse the world's large language models. Compare parameters, benchmarks, VRAM and more.
This is an utility repo for testing inference methods. Please use bigscience/bloom to access the latest model.
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.
1. Model Summary 2. Use 3. Training 4. License 5. Citation
One of the focus areas at Together Research is new architectures for long context, improved training, and inference performance over the Transformer architecture. Spinning out of a research program from our team and academic collaborators, with roots in signal processing-inspired…
CAT-Paws is an agentic LLM that thinks in Japanese (e.g., reasoning trace is in Japanese). The model is based on Qwen3-Swallow-v0.2 which is a continual pretraining model based on Qwen3 to read and write fluently in Japanese.
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.
This model card introduces a moderation model, a GPT-JT model fine-tuned on Ontocord.ai's OIG-moderation dataset v0.1.
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).
Overview This repository provides an English-Japanese bilingual GPT-NeoX model of 3.8 billion parameters.
0. TL;DR 1. Model Details 2. Training Details 3. Usage 4. Evaluation 5. Citation
Overview We conduct continual pre-training of qwen-14b on 66B 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…
We present GoLongRL, a fully open-source, capability-oriented post-training recipe for long-context reinforcement learning with verifiable rewards (RLVR).