RealRobot_chatbot_llm is a professional product artificial intelligence model based on the Gemma3n architecture, specifically fine-tuned on the proprietary dataset of the RealRobot product catalog. This model can quickly create an accurate, cost-effective, and deployable professional language model based on the enterprise's own product data, providing highly specialized product Q&A services.

Natural Language ProcessingGgufMultiple Languages

MiniMax-M2 is a small Mixture of Experts (MoE) model built specifically for maximizing coding and agent workflows. It has a total of 230 billion parameters, with 1 billion active parameters. This model excels in coding and agent tasks while maintaining strong general intelligence. It is compact, fast, and cost-effective.

Natural Language ProcessingTransformers

MiniMax-M2 is a small Mixture of Experts (MoE) model built specifically for maximizing coding and agent workflows. It has a total of 230 billion parameters, with only 10 billion parameters activated. It performs excellently in coding and agent tasks while maintaining strong general intelligence, featuring compactness, speed, and cost-effectiveness.

Natural Language ProcessingTransformers

MiniMax-M2 is a 'mini' model built specifically for maximizing coding and agent workflows. It is a compact, fast, and cost-effective Mixture of Experts (MoE) model that excels in coding and agent tasks while also possessing strong general intelligence.

Natural Language ProcessingTransformers

MiniMax-M2 is a 'mini' model specifically built to maximize coding and agent workflows. It adopts a Mixture of Experts architecture, with a total of 230 billion parameters and 10 billion active parameters. This model excels in coding and agent tasks while maintaining strong general intelligence. It is compact, fast, and cost-effective.

Natural Language ProcessingTransformers

ContentV is an efficient video generation model framework that achieves high-quality video generation with limited computing resources through a minimalist architecture, multi-stage training strategy, and cost-effective reinforcement learning framework.

Computer VisionDiffusers

OpenVision is a fully open, cost-effective family of advanced visual encoders focused on multimodal learning.

MultimodalOpenclip

OpenVision is a fully open, cost-effective advanced vision encoder family focused on multimodal learning.

MultimodalOpenclip

OpenVision is a fully open, cost-effective family of advanced vision encoders designed for multimodal learning.

Computer VisionTransformers

OpenVision is a fully open, cost-effective family of advanced vision encoders for multimodal learning.

MultimodalOpenclip

OpenVision is a fully open-source, cost-effective advanced visual encoder family designed for multimodal learning, with performance matching or surpassing OpenAI CLIP.

MultimodalTransformers

OpenVision is a fully open, cost-effective family of advanced visual encoders, specifically designed for multimodal learning.

Computer VisionTransformers

OpenVision is a fully open, cost-effective family of advanced vision encoders focused on multimodal learning.

MultimodalOpenclip

OpenVision is a fully open, cost-effective family of advanced visual encoders focused on multimodal learning tasks.

Computer VisionTransformers

OpenVision is a fully open-source and cost-effective family of advanced visual encoders, specifically designed for multimodal learning.

MultimodalTransformers

OpenVision is a fully open, cost-effective family of advanced visual encoders focused on multimodal learning.

Computer VisionOpenclip

OpenVision-ViT-Tiny is a fully open, cost-effective advanced visual encoder, part of the OpenVision family, focusing on multimodal learning.

Computer VisionTransformers

OpenVision is a fully open, cost-effective family of advanced vision encoders focused on image feature extraction in multimodal learning.

MultimodalOpenclip

OpenVision is a fully open-source, cost-effective family of advanced vision encoders for multimodal learning.

MultimodalOpenclip

OpenVision is a fully open, cost-effective family of advanced vision encoders focused on multimodal learning.

MultimodalOpenclip