This project provides a quantized version of the cerebras/MiniMax-M2-REAP-172B-A10B model, aiming to make knowledge accessible to the public. This is a large language model with 172 billion parameters, which has been optimized and quantized to reduce deployment costs and improve inference efficiency.

Natural Language ProcessingGguf

This model is a knowledge distillation model based on the Qwen3-4B architecture, trained with approximately 54.4 million tokens generated by Gemini 2.5 Flash, aiming to integrate the behavior, inference process, and knowledge of Gemini-2.5 Flash into a single dataset.

Natural Language ProcessingTransformersEnglish

Trouper-12B GGUF is a text generation model developed by DarwinAnim8or based on the original model. It is specifically optimized for role-playing and creative writing scenarios. This model is fine-tuned from Mistral-Nemo-Base-12B and trained using a custom 'Actors' dataset. The generated text is more natural and avoids the common 'AI language' features.

Natural Language ProcessingGgufEnglish

FLAN-T5 Small is an instruction fine-tuned text generation model developed by Google, based on the small version of the T5 architecture. This model has undergone instruction fine-tuning on various NLP tasks and can understand and execute various text generation instructions.

Natural Language ProcessingSafetensorsEnglish

This project is based on the moonshotai/Kimi-K2-Thinking base model. The original INT4 model is converted into a higher-quality text generation model through a custom anti-quantization script, aiming to make knowledge accessible to everyone.

Natural Language ProcessingGguf

This is a quantized version model based on Moonshot AI technology, focusing on visual language understanding and generation tasks, and committed to lowering the threshold of knowledge acquisition and making knowledge accessible to everyone.

Natural Language ProcessingGguf

Kimi K2 Thinking is the latest generation of open-source thinking model developed by Moonshot AI. It has powerful deep reasoning ability and tool call function. The model adopts a mixture-of-experts architecture, supports native INT4 quantization, has a 256k context window, and performs excellently in multiple benchmark tests.

Natural Language ProcessingTransformers

This is a fine-tuned AI model designed specifically for students in the School of Science and Technology at the University of Saint Simon. It is integrated into the TecnoTime application to help students stay organized in their studies, improve academic continuity, and reinforce learning habits through structured notifications and motivational messages.

Natural Language ProcessingSafetensorsMultiple Languages

SDXL-Deepfake-Detector is a tool for accurately detecting AI-generated faces. It focuses on maintaining the authenticity of the digital world and provides a privacy-protected and open-source solution to combat visual misinformation. This model achieves lightweight and highly accurate detection through fine-tuning a pre-trained model.

Computer VisionSafetensors

JanusCoder-14B is an open-source foundation model with 14B parameters built on Qwen3-14B, aiming to establish a unified visual programming interface for code intelligence. This model is trained on the JANUSCODE-800K multimodal code corpus and can handle various visual programming tasks in a unified manner.

Natural Language ProcessingTransformers

JanusCoder-8B is an open-source code intelligence foundation model built on Qwen3-8B, aiming to establish a unified visual programming interface. This model is trained on JANUSCODE-800K (the largest multimodal code corpus to date) and can handle various visual programming tasks, including data visualization, interactive web UI, and code-driven animation.

MultimodalTransformers

This is an experimental pre-trained model based on RouWei-0.8, adopting a 16-channel latent space architecture and using a Flux autoencoder. The model aims to achieve finer image details at a lower computational cost while retaining the knowledge and performance of the original model.

Computer VisionDiffusersEnglish

Qwen3-VL-2B-Instruct is the most powerful vision-language model in the Qwen series. It has excellent text understanding and generation capabilities, in-depth visual perception and reasoning abilities, long context support, and strong spatial and video dynamic understanding abilities. This model uses a 2B parameter scale, supports instruction interaction, and is suitable for multimodal AI applications.

MultimodalTransformers

This is an AI model specifically designed for Python code review. It is fine-tuned based on Qwen2.5 - 7B - Instruct and can identify security vulnerabilities, performance issues, and provide suggestions for code quality improvement.

Natural Language ProcessingTransformersEnglish

This project is a quantized version based on the MiniMaxAI/MiniMax-M2 model, aiming to make knowledge accessible to the public. It provides multiple model versions with different quantization levels and shows the perplexity performance indicators of each version.

Natural Language ProcessingGguf

Omni L1B3RT4S GENIE is an AI assistant fine-tuned based on the Qwen2.5-3B Instruct architecture. It is trained with customized examples of 1,103 elf characters, and has unique voice and loyalty modes, capable of providing users with a unique dialogue experience.

Natural Language ProcessingGgufEnglish

This project is a quantized version based on the IBM Granite-4.0-h-350m model, aiming to make knowledge accessible to everyone. This model is an efficient text generation model. After quantization optimization, it has a smaller model size and faster inference speed.

Natural Language ProcessingGguf

This is a LoRA model for flight and bullet time video effects based on Wan2.1, specifically designed to generate images with bullet time effects, capable of creating a unique visual effect where a character floats in the air and the camera perspective rotates around the character.

Computer VisionDiffusers

SecInt is a SmolLM2-360M model fine-tuned for real-time nginx security log classification, aiming to automatically detect security threats, errors, and normal traffic patterns in web server logs with an accuracy of over 99%, enabling real-time detection on the CPU.

Natural Language ProcessingTransformersMultiple Languages

VieNeu-TTS is the first Vietnamese text-to-speech model that can run on personal devices and has the ability of instant voice cloning. Fine-tuned based on NeuTTS Air, it can generate natural and realistic Vietnamese speech and has real-time performance on the CPU.

Audio ProcessingSafetensorsOther