# Instruction Tuning Optimization

OpenELM is a series of efficient language models introduced by Apple, utilizing a hierarchical scaling strategy to optimize parameter allocation, offering pretrained and instruction-tuned models ranging from 270M to 3B parameters.

A Japanese vision-language model based on Llama-3-8B-Instruct, enhanced with additional pretraining and instruction tuning for improved Japanese capabilities

magnum-v2-12b is the fourth model in the series, aiming to replicate the text quality of the Claude 3 series models (especially Sonnet and Opus). It is fine-tuned based on Mistral-Nemo-Base-2407 and has powerful text generation capabilities.

Llama-3-8B-Instruct-RR is a model based on Llama-3. It uses Representation Re-routing (RR) technology to insert circuit breakers, aiming to reduce the generation of harmful content while maintaining the model's capabilities.

Cambrian is an open-source multimodal LLM (Large Language Model) designed with a vision-centric approach.

RecurrentGemma is an open language model family developed by Google based on a novel recurrent architecture, offering both pre-trained and instruction-tuned versions suitable for various text generation tasks.