# Multilingual instruction following

Granite-3.3-8B-Instruct is an 8-billion-parameter language model supporting 128K context length, specifically fine-tuned to enhance reasoning and instruction-following capabilities.

A 24B parameter instruction-tuned model by Mistralai, supporting 128k context length and multilingual processing, enhanced with Neo Imatrix technology and MAX quantization scheme

Falcon3-10B-Instruct is an open-source foundational model from the Falcon3 series, featuring 10 billion parameters, specializing in high-quality instruction-following tasks, supporting multilingual processing with a context length of up to 32K tokens.

This is a quantized version in GGUF format converted from the Meta Llama-3.2-1B-Instruct model, suitable for local inference scenarios.

Japanese-enhanced large language model optimized based on the Llama 2 series, with improved instruction-following capabilities through supervised fine-tuning

This is a 7-billion-parameter Tamil large language model enhanced based on LLaMA-2, supporting text generation tasks in both Tamil and English.

A 1.3B parameter instruction-following large language model developed by 42dot, based on the supervised fine-tuned version of LLaMA 2 architecture