# Multi-round dialogue

Chinda LLM 4B is a cutting-edge Thai model launched by iApp Technology, built on the Qwen3-4B architecture, bringing advanced thinking capabilities to the Thai AI ecosystem.

This is an 8-bit quantized version in MLX format converted from the DeepSeek-R1-0528-Qwen3-8B model, suitable for text generation tasks.

A large language model for Arabic logical reasoning fine-tuned based on Qwen3-14B, optimized specifically for enhancing Arabic logical reasoning ability

This model is a 4-bit DWQ quantized version of Qwen3-4B, converted to the MLX format for easy text generation using the mlx library.

xLAM-2-3b-fc-r is a large action model with 3B parameters launched by Salesforce, focusing on transforming user intentions into executable actions and performing excellently in multi-round dialogue and tool usage.

This project adapts the T-lite-it-1.0 model to Russian. By replacing the tokenizer, continuing pre-training on the Russian corpus, and applying LEP technology, the generation speed of Russian text is improved.

This project is the result of adapting the model to Russian. By replacing the tokenizer, continuing pre-training on the Russian corpus, and applying LEP technology, the generation speed of Russian text has been improved, providing a new solution for Russian natural language processing.

This is a version of the openchat/openchat-3.6-8b-20240522 model after Llama.cpp imatrix quantization. It provides files of different quantization types, making it convenient for users to download and use according to their needs.

InternLm-ChatBode is a language model fine-tuned for Portuguese, developed based on InternLM2 and optimized with the UltraAlpaca dataset.

Mistral 7B Instruct v0.2 is an instruction fine-tuned version based on the Mistral 7B model, suitable for text generation tasks.

OpenChat is a series of open-source language models that have been fine-tuned on diverse and high-quality multi-round dialogue datasets, aiming to achieve high performance with limited data.