# Reinforcement learning alignment

Llama-3.3-Nemotron-Super-49B-v1-FP8 is a large language model derived from Meta Llama-3.3-70B-Instruct, optimized to enhance reasoning capabilities, conversational preferences, and task execution, supporting a context length of 128K tokens.

Meta Llama 3.3 is a 70-billion-parameter multilingual large language model optimized for multilingual dialogue scenarios, supporting 8 languages and excelling in multiple benchmark tests.

GGUF quantized version based on Meta's official Llama 3 70B instruction fine-tuned model, supporting 2-16bit multiple quantization levels, suitable for locally deployed dialogue scenarios

Xwin-LM is a large language model developed based on Llama2, focusing on alignment technology research and demonstrating excellent performance in the AlpacaEval benchmark.

Llama 2 is a series of generative text models open-sourced by Meta, including pre-trained and dialogue fine-tuned versions ranging from 7 billion to 70 billion parameters. This model is the 7 billion parameter dialogue-optimized version, fine-tuned with reinforcement learning for dialogue scenarios.

Llama 2 is Meta's open-source 13-billion-parameter conversation-optimized large language model, aligned with human preferences using RLHF, supporting 4k context length