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 project is a quantized version of TheDrummer's Cydonia-24B-v4.3 model. It uses llama.cpp for quantization processing, aiming to provide model files of different quantization types to meet the needs of different hardware and performance. It is a large language model with 24B parameters, mainly used for text generation tasks.

Natural Language ProcessingGguf

Z-Image-Re-Turbo is a text-to-image generation model that has been optimized for de-reduction and re-acceleration based on the Z-Image-De-Turbo model. This model aims to balance the convenience during training and the speed during inference. It restores the fast generation ability close to the original Turbo model while maintaining the same training-friendly features as Z-Image-De-Turbo, enabling it to be perfectly compatible with a large number of trained LoRA models in the Z-Image ecosystem.

MultimodalDiffusers

This is the GGUF quantized version of the large language model Mistral-Large-3-675B-Instruct-2512 developed by Mistral AI. The original model has 675 billion parameters and is designed for instruction-following tasks. This project uses the llama.cpp tool and combines it with the imatrix calibration dataset to generate more than 20 different precision quantized model files from Q8_0 to IQ1_S, aiming to balance model performance, inference speed, and storage/memory usage, enabling it to run on a wider range of hardware.

Natural Language ProcessingGgufMultiple Languages

This model is an MLX format conversion version of the Ministral-3-3B-Instruct-2512 instruction fine-tuning model released by Mistral AI. It is a large language model with a parameter scale of 3B, specifically optimized for following instructions and dialogue tasks, and supports multiple languages. The MLX format enables it to run efficiently on Apple Silicon devices.

Natural Language ProcessingMlxMultiple Languages

This model is obtained through distillation training using the high-reasoning-difficulty Gemini 3 Pro preview dataset based on the Qwen3-4B-Thinking-2507 base model. It focuses on improving complex reasoning abilities in the fields of coding and science. Through training with specific datasets, it aims to efficiently transfer the reasoning abilities of large models (such as Gemini 3 Pro) to a smaller-scale model.

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

VibeThinker-1.5B is a 1.5-billion-parameter dense language model launched by Weibo AI. It is fine-tuned based on Qwen2.5-Math-1.5B and is specifically designed for mathematical and algorithmic coding problems. Trained using the 'Spectrum to Signal Principle' framework, it outperforms larger models in multiple math competition tests. The training cost is approximately $7,800, and it supports an output of up to about 40k tokens.

Natural Language ProcessingTransformersMultiple Languages

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

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

Gaperon-1125-24B is a bilingual (French-English) language model with 24 billion parameters. It has been trained on approximately 2 trillion tokens and can proficiently handle French, English, and coding tasks. This model uses the OLMo-2 architecture, aiming to achieve the best balance between large-scale, high-quality text generation and excellent task performance.

Natural Language ProcessingTransformersMultiple Languages

TheWhisper-Large-V3-Turbo is a high-performance fine-tuned version of the OpenAI Whisper Large V3 model, optimized by TheStage AI for real-time, low-latency, and low-power speech-to-text inference across multiple platforms. It supports stream transcription, word timestamps, and scalable performance, making it suitable for scenarios such as real-time subtitles, meetings, and device-side voice interfaces.

Audio ProcessingTransformersOther

TheWhisper-Large-V3 is a high-performance fine-tuned version of the OpenAI Whisper Large V3 model, optimized by TheStage AI for real-time, low-latency, and low-power consumption speech-to-text inference on multiple platforms (NVIDIA GPU and Apple Silicon).

Audio ProcessingTransformersOther

PokeeResearch - 7B is a 7 - billion - parameter in - depth research agent model developed by Pokee AI. It combines Reinforcement Learning from AI Feedback (RLAIF) and a powerful reasoning framework, enabling reliable, aligned, and scalable research - level reasoning in tool - enhanced large language models. It is suitable for complex multi - step research workflows.

Natural Language ProcessingTransformersEnglish

KaniTTS is a high-speed, high-fidelity text-to-speech model optimized for real-time conversational AI applications. It uses a two-stage pipeline combining a large language model and an efficient audio codec to achieve excellent speed and audio quality. This model supports Spanish, has 400 million parameters, and a sampling rate of 22kHz.

Audio ProcessingTransformersSpanish

KaniTTS is a high-speed, high-fidelity Arabic text-to-speech model optimized for real-time conversational artificial intelligence applications. It adopts a two-stage pipeline architecture, combining a large language model with an efficient audio codec to achieve excellent speed and audio quality, and can meet the speech synthesis needs of multiple fields such as conversational AI, accessibility assistance, and research.

Audio ProcessingTransformersArabic

KaniTTS is a high-speed, high-fidelity text-to-speech model optimized for real-time conversational AI applications. Through a unique two-stage architecture that combines a large language model with an efficient audio codec, it achieves low-latency and high-quality speech synthesis, with a real-time factor as low as 0.2, which is 5 times faster than real-time speed.

Audio ProcessingTransformersEnglish

KaniTTS Pretrain v0.3 is a high-speed, high-fidelity text-to-speech model optimized for real-time conversational AI applications. It uses a two-stage pipeline architecture that combines a large language model and an efficient audio codec to achieve extremely low latency and high-quality speech synthesis.

Audio ProcessingTransformersMultiple Languages

Bee-8B is an advanced fully open-source multimodal large language model that focuses on data quality and aims to narrow the performance gap with proprietary models. By using the high-quality Honey-Data-15M corpus and the advanced data processing pipeline HoneyPipe, it demonstrates excellent performance in complex reasoning and other aspects.

MultimodalTransformersEnglish

Apriel-1.5-15b-Thinker is a multimodal reasoning model developed by the ServiceNow SLAM Lab, with a parameter scale of 15 billion. It has powerful text and image understanding and reasoning capabilities, adopting a chained reasoning mode of 'think-answer', aiming to achieve performance comparable to large models with a smaller model scale.

MultimodalTransformers