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

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

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

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

This project performs MXFP4_MOE quantization on the Qwen3-VL-235B-A22B-Thinking model, aiming to provide more efficient image text-to-text conversion capabilities. This version is from unloth, and the context size has been extended from 256k to 1M. The model's performance in different scenarios is optimized through specific quantization techniques.

MultimodalGguf

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 project provides a quantized version of the Huihui Qwen3-VL-30B-A3B-Instruct model, aiming to improve the performance and efficiency of the model in specific scenarios. This is a visual language model based on the Qwen3-VL architecture, supporting multimodal interaction between images and text.

MultimodalGguf

This is the MXFP4_MOE quantized version of the Huihui AI model Huihui-MoE-60B-A3B-abliterated, which provides support for text generation. This quantized version is processed based on a specific base model and can optimize the model's performance and user experience to a certain extent.

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

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

Apertus is a fully open multilingual large language model developed by Swiss AI, offering two parameter scales of 7 billion and 8 billion. This model supports over 1000 languages, uses fully compliant and open training data, and its performance can rival that of closed-source models. Apertus was pre-trained on 15T tokens and adopts a phased curriculum training method, supporting a context length of up to 65,536 tokens.

Natural Language ProcessingTransformersOther

This project provides a quantized version of zai-org/GLM-4.6, aiming to make knowledge accessible to everyone. It is a text generation model optimized based on the original GLM-4.6 model, offering more efficient inference performance.

Natural Language ProcessingGguf

Apertus is a fully open multilingual large language model developed by Swiss AI. It has parameter scales of 8 billion and 70 billion, supports over 1000 languages and long context processing, and only uses fully compliant open training data. Its performance can rival that of closed-source models.

Natural Language ProcessingTransformersOther

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

GLM-4.6 is a new-generation text generation model launched by Zhipu AI. Compared with GLM-4.5, it has significant improvements in multiple aspects, including a longer context window, better coding performance, and stronger reasoning ability. This model performs excellently in multiple public benchmark tests and has a competitive advantage compared with leading models at home and abroad.

Natural Language ProcessingTransformersMultiple Languages

GLM-4.6 is a new-generation large language model developed by Zhipu AI. Compared with GLM-4.5, it has significant improvements in context processing, coding ability, and reasoning performance. This model supports a context length of 200K and performs excellently in multiple public benchmark tests, especially having competitive advantages in code generation, reasoning, and agent tasks.

Natural Language ProcessingTransformersMultiple Languages

GLM-4.6 is a new-generation text generation model launched by Zhipu AI. Compared with GLM-4.5, it has achieved significant improvements in context processing, encoding performance, reasoning ability, etc. It supports a context length of 200K and has stronger agent capabilities and refined writing abilities.

Natural Language ProcessingTransformersMultiple Languages

GLM-4.6-FP8 is a new-generation text generation model launched by Zhipu AI. It has significant improvements in multiple key aspects compared to GLM-4.5. This model has a longer context window, excellent coding performance, advanced reasoning ability, and more powerful agent functions, enabling it to handle more complex tasks.

Natural Language ProcessingTransformersMultiple Languages

CoDA is a code generation language model based on diffusion models developed by Salesforce AI Research. It has the ability to understand bidirectional context and is specifically designed for powerful code generation and completion tasks. This model only has 1.7 billion parameters and achieves excellent code generation performance while maintaining low computational requirements.

Natural Language ProcessingTransformersEnglish