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The Mistral-Nemo-Instruct-2407 Large Language Model (LLM) is an instruct fine-tuned version of the Mistral-Nemo-Base-2407. Trained jointly by Mistral AI and NVIDIA, it significantly outperforms existing models smaller or similar in size.

A roleplaying model that is good at following context, realistically portraying characters, and responding creatively. Performs especially well for its size.

Finetuned from Llama 3.1, with better instruction following and character personification. Performs well in a variety of languages.

Second in the Lotus series of high-EQ (emotional intelligence) models by FallenMerick, based on Mistral Nemo. They aim at high quality inference of communication styles to predict mood and add realism to characters' personalities.

Group-chat based roleplaying model trained on an entirely human-based dataset, based on forum/internet group roleplaying styles.

A direct replacement/successor to Euryale v2.2, entirely trained on top of Llama 3.3 Instruct.

Research release of a 104 billion parameter highly performant generative model optimized for reasoning, summarization, and question answering. Command-R supports multilingual generation in 10 languages and has RAG capabilities.

First in a series of models designed to replicate the prose quality of the Claude 3 models, specifically Sonnet and Opus. This model is fine-tuned on top of Qwen-2 72B Instruct.

The one and only Space Whale, remastered and requantized in full 32-bit precision. Should be a dramatic improvement over the classic Psyonic Cetacean 20B in terms of creativity and quality of inference.

Version 3.3 of the popular Stheno series, capable of 32K context. A model made for 1-on-1 roleplay, but also able to handle scenarios, RPGs and storywriting. Uncensored during actual roleplay scenarios.

Uncensored Llama2 model that was designed for roleplaying and storytelling and excels at both. The model performs well at other tasks and responds well to changes in the prompt.

Llama3-based RP and Storytelling model by Hastagaras, with DPO and LORAs applied to reduce cheerfulness and emoji.