This is a quantized version of TheDrummer's Magidonia-24B-v4.3 large language model. By using the imatrix quantization technology of llama.cpp, GGUF format files with various precisions from BF16 to IQ2_XS are generated, aiming to run the model more efficiently under different hardware conditions (especially in resource-constrained environments) while maintaining the model performance as much as possible.

Natural Language ProcessingGguf

This is a quantized version of ai-sage's GigaChat3-10B-A1.8B model, using the imatrix quantization technology of llama.cpp, which can run more efficiently under different hardware conditions. The model supports Russian and English and is mainly used for text generation tasks.

Natural Language ProcessingGgufMultiple Languages

This is an experimental quantized version of the dense model based on Qwen3-4B-Thinking-2507. It adopts the innovative MXFP4 mixed quantization technology, aiming to explore the combination of weights with different precisions (such as MXFP4, Q8_0, Q6_K, etc.) to significantly reduce the model file size, improve the inference speed (TPS), and at the same time, maintain the precision as close as possible to the original F16 model. This project demonstrates the potential of the mixed quantization method, but it has been replaced by the author's updated version.

Natural Language ProcessingSafetensorsOther

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

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

This is a quantized version of the Alibaba Tongyi Deep Research 30B-A3B model. It uses MXFP4_MOE quantization technology and additionally adds imatrix quantization, aiming to optimize model performance and resource utilization efficiency, and is suitable for text generation tasks.

Natural Language ProcessingGguf

This is a quantized version of the KAT-Dev model of Kwaipilot, processed using the imatrix quantization technology of llama.cpp, aiming to improve the running efficiency and performance of the model in different hardware environments. This version offers multiple quantization levels, from high quality to extreme compression, to meet different memory and computing resource requirements.

Natural Language ProcessingGguf

GLM-4.6-AWQ is a model that performs high-performance AWQ quantization on Zhipu AI's GLM-4.6 (357B MoE). It is optimized for vLLM inference and can effectively improve the throughput of production deployment. This model uses 4-bit quantization technology, which significantly reduces video memory usage while maintaining high accuracy.

Natural Language ProcessingTransformersMultiple Languages

lans_v1 - lora is a text-to-image conversion model trained using the AI Toolkit by Ostris based on the Qwen/Qwen-Image model. It is optimized using LoRA technology and has good image generation capabilities.

MultimodalDiffusers

This is a quantized version based on the swiss-ai's Apertus-70B-Instruct-2509 model. Multiple quantized model files are generated using the imatrix technology of llama.cpp, aiming to improve the model's running efficiency and resource utilization, and support flexible selection of suitable quantization levels under different hardware conditions.

Natural Language ProcessingGguf

pejawan22-lora is a LoRA model trained based on AI technology, specifically designed for generating specific images and can be integrated with various AI tools. Images are generated by the trigger word 'peja'.

MultimodalDiffusers

This is a quantized version of the IBM Granite 4.0 Micro model, optimized using the imatrix technology of llama.cpp. It aims to improve the running efficiency and performance of the model in specific environments. This version offers multiple quantization levels, suitable for different hardware configurations and usage scenarios.

Natural Language ProcessingGguf

This is a text-to-video LoRA model based on AI technology, specifically optimized and trained for the Alita character. It can be used in scenarios such as image generation, providing convenience for applications in related fields.

MultimodalDiffusers

piccoli_no_style-lora is a LoRA model based on image-to-video technology, trained using AI Toolkit. It is mainly used for image generation tasks and can be used in conjunction with various mainstream AI tools.

Computer VisionDiffusers

piccoli_no_style-lora is a generative model based on image-to-video and LoRA technology. It is trained using AI Toolkit and is based on the Qwen/Qwen-Image model. It supports various image generation scenarios.

MultimodalDiffusers

This is an image-to-video LoRA model trained based on the Qwen/Qwen-Image base model. It uses the LoRA (Low-Rank Adaptation) technology to achieve efficient fine-tuning and can be used for related tasks such as AI image generation.

MultimodalDiffusers

Llama-3.1-8B-onnx-ryzenai-npu is an optimized version developed by AMD based on Meta's Llama-3.1-8B model, specifically optimized for deployment on the AMD Ryzen AI NPU. Through Quark quantization, OGA model builder, and NPU-specific post-processing technology, this model significantly improves the inference efficiency on AMD hardware while maintaining high-quality text generation capabilities.

Natural Language ProcessingOnnxEnglish

This project is a quantized version of swiss-ai/Apertus-8B-Instruct-2509, aiming to make knowledge models more accessible and usable through quantization technology. The project is currently in the experimental stage and uses the GGUF format for optimization.

Natural Language ProcessingGguf

This project is the A3B quantized version of Alibaba's Tongyi In-depth Research 30B model. It aims to reduce the model deployment cost through quantization technology and make knowledge accessible to everyone. This model is optimized based on a large language model with a scale of 30B parameters, maintaining the strong capabilities of the original model while improving the inference efficiency.

Natural Language ProcessingGguf

This is the quantized version of the Tesslate/UIGEN-FX-4B-Preview model, aiming to make large language models easier to deploy and use through quantization technology, realizing the concept of 'Making knowledge accessible to everyone'.

Natural Language ProcessingGguf