This is a quantized version of the vanta-research/atom-v1-preview-12b model, offering a variety of quantization types. It is suitable for multiple scenarios such as dialogue, collaboration, and education. This model is based on the Gemma architecture and supports English language processing.

MultimodalTransformersEnglish

atom-v1-preview-12b is a quantized version based on the vanta-research/atom-v1-preview-12b base model, offering multiple GGUF quantization format options, suitable for multiple domains such as dialogue, collaboration, and education.

Natural Language ProcessingTransformersEnglish

Qwen3-32B is the latest generation of large language models in the Qwen series, with powerful reasoning, instruction-following, intelligent agent interaction, and multilingual processing capabilities. It supports over 100 languages and dialects and can seamlessly switch between thinking and non-thinking modes, providing users with a natural and smooth dialogue experience.

Natural Language ProcessingTransformers

This project is a high-quality HQ4_K quantization of the MiniMax-M2 model, optimized specifically for text generation tasks and particularly suitable for dialogue scenarios. This quantized version does not use imatrix and maintains the model's performance.

Natural Language ProcessingGguf

MOSS-TTSD is an open-source bilingual spoken dialogue synthesis model that supports Chinese and English. It can convert two-person dialogue scripts into natural and expressive dialogue voices. It supports voice cloning, and the maximum duration of single-round voice generation can reach 1700 seconds.

Audio ProcessingSafetensorsMultiple Languages

Hebrew_Nemo is a large language model focused on Hebrew processing. It has undergone instruction fine-tuning and supports text generation and dialogue interaction. This version is the GGUF quantized version of the original model, offering multiple quantization levels.

Natural Language ProcessingTransformersMultiple Languages

This is a quantized version based on the SicariusSicariiStuff/Hebrew_Nemo model, a large language model with the Mistral architecture specifically optimized for Hebrew, supporting text generation and dialogue tasks in Hebrew and English.

Natural Language ProcessingTransformersMultiple Languages

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 is the MLX format conversion version of the Qwen3-Next-80B-A3B-Instruct model, optimized for efficient operation on Apple Silicon devices. The model is a large language model with 80 billion parameters, supporting text generation tasks and having powerful dialogue and reasoning capabilities.

Natural Language ProcessingMlx

This is the 4-bit quantized version of the Qwen3-VL-4B-Instruct model, specifically optimized for Apple Silicon chips and converted using the MLX framework. This model is a vision-language model that supports image understanding and multimodal dialogue tasks.

MultimodalMlx

This is a visual language model in MLX format converted from the Qwen3-VL-30B-A3B-Thinking model, supporting image understanding and multimodal dialogue, and optimized with bf16 precision.

MultimodalMlx

Qwen3-VL-4B-Instruct is a 4-billion-parameter instruction-tuned multimodal large language model launched by the Alibaba Cloud Qwen team. It is optimized for Qualcomm NPUs, integrating powerful visual-language understanding capabilities with dialogue fine-tuning functions, and is suitable for practical application scenarios such as chat reasoning, document analysis, and visual dialogue.

MultimodalGguf

Qwen2.5-14B-Instruct is a multilingual large language model based on the Qwen2.5 architecture, with 14 billion parameters. It supports 13 languages and has excellent instruction-following and dialogue capabilities. This model performs well in various language tasks and is suitable for text generation and understanding in multilingual scenarios.

Natural Language ProcessingTransformersMultiple Languages

ArcMind is a next - generation dialogue model developed by ArcDevs, focusing on natural interaction, adaptive intelligence, and context precision, aiming to provide users with a seamless, human - like dialogue experience.

Natural Language ProcessingTransformersEnglish

DIMI Arabic OCR v2 is an optical character recognition model specifically optimized for Arabic text recognition. It is developed based on fine-tuning Qwen2.5-VL-7B-Instruct and has significant improvements in handling texts with dense diacritics compared to the v1 version.

MultimodalPeftArabic

A high-quality quantized version of GLM-4.6, implemented using advanced quantization techniques without using imatrix, maintaining good model performance and compatibility, suitable for various application scenarios such as dialogue.

Natural Language ProcessingGguf

Sungur-14B is a large language model specifically designed for Turkish, derived from Qwen/Qwen3-14B. The model is fine-tuned using a dataset containing 41,100 Turkish samples, covering reasoning dialogues in fields such as mathematics, medicine, and general knowledge, aiming to enhance the native reasoning ability in Turkish.

Natural Language ProcessingGgufOther

This is a vision-language model converted from the Huihui-GLM-4.5V-abliterated model, using the MXFP4 quantization format and specifically optimized for the Apple MLX framework. It supports image understanding and multimodal dialogue tasks.

MultimodalMlxMultiple Languages

EchoVLM is a dynamic mixture of experts vision-language model designed specifically for the medical ultrasound field. It can process image and text inputs and generate text outputs, and has important application value in ultrasound intelligent diagnosis.

MultimodalTransformersMultiple Languages

This is a quantized version based on diabolic6045/Sanskrit-qwen-7B-Translate-v2, specifically designed for Sanskrit translation and transliteration tasks. It offers multiple quantization types and supports translation and transliteration from English to Sanskrit, including both IAST and Devanagari formats.

Natural Language ProcessingTransformersEnglish