FLUX.2-dev is an image generation and editing model based on NF4 quantized DiT and text encoder, providing high-quality image generation and editing capabilities, suitable for development applications in the image field.

Computer VisionDiffusersEnglish

This is a quantized version of the squ11z1's Hypnos-i1-8B model, which is quantized using the llama.cpp tool and a specific dataset. The model is based on the Llama-3 architecture, offering multiple quantization type options and supporting text generation tasks. It is suitable for various application scenarios such as inference and dialogue.

Natural Language ProcessingGgufEnglish

Qwen3-VL-4B-Instruct is a 4-billion-parameter visual language model launched by Alibaba. It is developed based on the Qwen3 architecture and supports multimodal understanding and dialogue tasks. This model has powerful image understanding and text generation capabilities, and can handle complex visual language interaction scenarios.

MultimodalTransformers

This is an MXFP4_MOE imatrix quantized version based on the Huihui-MiroThinker-v1.0-30B model, specifically optimized for text generation tasks. It significantly reduces the model size and inference cost while maintaining model performance.

Natural Language ProcessingGguf

Cecilia FT MS v1 is a Cuban language model fine-tuned based on Cecilia 2B v0.1, specifically optimized for Cuban Spanish to capture the nuances of Cuban language, culture, and society. This model supports Spanish and English and is mainly used for text generation tasks.

Natural Language ProcessingTransformersMultiple Languages

FLUX.2 [dev] is a rectified flow transformer model with 32 billion parameters, specifically designed for image generation, editing, and composition tasks. This model leads in text-to-image generation, single-reference editing, and multi-reference editing, enabling character, object, and style referencing without fine-tuning, and supporting personal, scientific, and commercial use.

MultimodalDiffusersEnglish

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

The quantized GGUF version of Tencent's Hunyuan Video 1.5 model, specifically designed for text-to-video generation tasks, supports 720P HD video generation, and offers multiple quantization precision versions to optimize usage efficiency.

MultimodalGguf

This project provides a quantized GGUF version of Tencent's Hunyuan Video 1.5 text-to-video model, which supports 480P video generation tasks. It includes both distilled and full models and can be used in conjunction with tools such as ComfyUI-GGUF.

MultimodalGguf

This is a statically quantized version of the wexyyyyyy/Ru-Gemma3-1B model, supporting Russian and English, and is specifically designed for dialogue and text generation tasks. The model offers multiple quantized versions suitable for different hardware configurations and performance requirements.

Natural Language ProcessingTransformersMultiple Languages

Strawberry_Smoothie-TEST is a hybrid model obtained by merging three 12B parameter models using the mergekit tool. It combines the advantages of Unity-12B, Chaos-Unknown-12b, and Smoothie-12B-Model_Stock, aiming to provide better text generation and dialogue capabilities.

Natural Language ProcessingTransformers

This is the quantized version of the ai-sage/GigaChat3-702B-A36B-preview-bf16 model, aiming to provide the public with a free way to access knowledge. This model is a large language model focusing on text generation tasks.

Natural Language ProcessingGguf

This is a quantized version based on the Huihui-MiroThinker-v1.0-8B model, specifically optimized for text generation tasks. It improves inference efficiency through quantization technology while maintaining the model's performance.

Natural Language ProcessingGguf

This is a version of the MiroThinker-v1.0-30B model quantized using MXFP4_MOE imatrix, implemented based on mradermacher's imatrix. This quantized model maintains the text generation ability of the original model while improving inference efficiency through quantization technology. It is suitable for various application scenarios that require efficient text generation.

Natural Language ProcessingGguf

This is a large language model with 139B parameters obtained by uniformly pruning 40% of the experts in MiniMax-M2 using the REAP method. It adopts the GLM architecture and Mixture of Experts (MoE) technology, and undergoes various quantization processes through llama.cpp, suitable for text generation tasks.

Natural Language ProcessingGgufEnglish

This model is a large language model fine-tuned on a specific dataset based on meta-llama/Llama-3.1-70B-Instruct. It is specifically designed for text generation tasks and achieved a loss value of 0.6542 on the evaluation set.

Natural Language ProcessingPeft

Hunyuan Video-1.5 is a lightweight and high-performance video generation model. With only 8.3 billion parameters, it can provide top-notch video quality, significantly lowering the usage threshold. It can run smoothly on consumer-grade GPUs, supporting text-to-video and image-to-video generation, enabling every developer and creator to use it easily.

MultimodalDiffusersMultiple Languages

VibeThinker-1.5B-GGUF is the GGUF quantized version of the WeiboAI/VibeThinker-1.5B model, quantized by MaziyarPanahi. This model is a text generation model with 1.5B parameters, supporting multiple quantization levels (from 2-bit to 8-bit), which facilitates efficient operation on various hardware.

Natural Language ProcessingGguf

This project provides a static quantized version of the Qwen-4B-Instruct-2507-Self-correct model, supporting tasks such as text generation, bias mitigation, and self-correction. Based on the Qwen-4B architecture, the model has undergone instruction fine-tuning and self-correction training, offering multiple quantized versions to meet different hardware requirements.

Natural Language ProcessingTransformersEnglish

This is an English-Spanish translation model fine-tuned on the Amazon dataset based on the Google mT5-small model, specifically designed for text abstract generation tasks. The model achieved scores of Rouge1: 16.44 and Rouge2: 8.04 on the evaluation set.

Natural Language ProcessingTransformers