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HuggingFaceTB/SmolLM2-1.7B-Instruct is a 1.7 billion parameter instruction-tuned AI language model designed to provide efficient and accurate responses for a wide range of tasks while maintaining a lightweight and accessible architecture.

mistralai/Mathstral-7B-v0.1 is a 7 billion parameter AI model optimized for mathematical reasoning and problem-solving, designed to deliver precise and efficient solutions across a variety of mathematical domains.

deepseek-ai/deepseek-math-7b-instruct is a 7 billion parameter AI model specifically designed to excel in mathematical reasoning and problem-solving tasks, providing accurate and detailed step-by-step solutions.

microsoft/Phi-3.5-mini-instruct is a lightweight AI language model optimized for instruction-based tasks, offering efficient performance and high-quality responses with a compact architecture.

Qwen/Qwen2.5-3B-Instruct is a powerful 3 billion parameter AI language model designed to deliver high-quality, human-like responses across a wide range of natural language processing tasks.

Qwen/Qwen2.5-0.5B-Instruct is a compact 500 million parameter AI language model optimized for generating human-like responses and assisting with various natural language understanding tasks.

Qwen/Qwen2.5-1.5B-Instruct is a 1.5 billion parameter AI language model designed to generate human-like responses based on user inputs.

VideoLLaMA3-7B-Image is a model designed for image understanding.

VideoLLaMA3-7B is a model designed for video understanding.

AI-powered tool for recognizing Turkish license plates from images.

InstructPix2Pix is a Stable Diffusion model trained to edit images from human-provided instructions.

PixArt-Σ consists of pure transformer blocks for latent diffusion: It can directly generate 1024px, 2K and 4K images from text prompts within a single sampling process.

Generate synchronized audio for videos using AI. Enhance video content with matching sound effects or create custom audio from text descriptions.

UltraPixel is designed to create exceptionally high-quality, detail-rich images at various resolutions, pushing the boundaries of ultra-high-resolution image synthesis.

Qwen2-7B-Instruct is a versatile large language model with 7 billion parameters, optimized for instruction-following tasks. It delivers high performance in natural language understanding, content generation, and complex reasoning, making it ideal for a wide range of AI-driven applications, from chatbots to educational tools.

Qwen2.5-Math-7B-Instruct is a large language model with 7 billion parameters, specialized in advanced mathematical problem-solving and reasoning. It is fine-tuned for instruction-based tasks and excels in fields like algebra, calculus, and quantitative analysis, making it suitable for research, education, and technical applications.

Qwen2.5-Math-1.5B-Instruct is a math-specialized large language model with 1.5 billion parameters, fine-tuned for solving complex mathematical problems and handling instruction-based tasks. It excels in areas like algebra, calculus, and numerical reasoning, making it ideal for educational tools and research applications.

Qwen2.5-Coder-7B-Instruct is a specialized large language model with 7 billion parameters, designed for code understanding and generation. Fine-tuned for instruction-based tasks, it supports multiple programming languages, making it ideal for coding assistance, code completion, and educational applications.

Qwen1.5-0.5B-Chat is a lightweight conversational AI model with 500 million parameters, designed for efficient and interactive chat-based applications. Despite its smaller size, it offers fast performance and reliable natural language understanding, making it ideal for real-time AI interactions on resource-constrained systems.

PHI-4 by Microsoft is an advanced large language model designed for precise natural language understanding and generation. It offers robust performance in complex conversational AI and NLP tasks, making it well-suited for enterprise and research applications.