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 an MLX format conversion version of the instruction fine-tuned version of Falcon-H1-34B-Instruct, optimized specifically for Apple Silicon (M series chips). It is based on the original Falcon-H1-34B-Instruct model and converted to an 8-bit quantization format compatible with the MLX framework through the mlx-lm tool, aiming to achieve efficient local inference on macOS devices.

Natural Language ProcessingTransformersMultiple Languages

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

GLM-4.5-Air-2bit is a 2-bit quantized version converted from Zhipu AI's GLM-4.5-Air model. It is optimized using the MLX format and can run efficiently on Apple chip devices. This model supports text generation tasks and has the characteristics of being lightweight and highly efficient.

Natural Language ProcessingMlxMultiple Languages

GLM-4.5-Air-8bit is an 8-bit quantized version converted from Zhipu AI's GLM-4.5-Air model, specifically optimized for the MLX framework. This model maintains the powerful natural language processing capabilities of the original version, while reducing memory usage and computational requirements through quantization technology, making it suitable for efficient operation on Apple Silicon devices.

Natural Language ProcessingMlxMultiple Languages

A large language model developed by DeepSeek AI, optimized with 4-bit quantization, suitable for Apple chip devices.

Natural Language ProcessingMlx

AIM-v2 is an image encoder model developed by Apple, based on a timm-compatible architecture, suitable for image feature extraction tasks.

Computer VisionTransformers

Open Genmoji is an open-source project aimed at replicating Apple's Genmoji feature using open-source technologies to generate emoji-style images.

Computer VisionDiffusers

AIMv2 is a series of vision models pretrained with multimodal autoregressive objectives, achieving outstanding performance in multiple multimodal understanding benchmarks.

Computer VisionJax

AIMv2 is a series of vision models pretrained with multimodal autoregressive objectives, demonstrating outstanding performance across multiple multimodal understanding benchmarks.

MultimodalJax

AIMv2 is a series of vision models based on multimodal autoregressive objective pretraining, excelling in multimodal understanding benchmarks

Computer VisionJax

AIMv2 is a series of vision models pretrained with multimodal autoregressive objectives, excelling in multimodal understanding benchmarks.

Computer VisionJax

AIMv2 is a series of vision models pretrained with multimodal autoregressive objectives, demonstrating excellent performance across multiple visual understanding benchmarks.

Computer VisionJax

AIMv2 is a series of vision models pretrained with multimodal autoregressive objectives, achieving outstanding performance across multiple vision understanding benchmarks.

Computer VisionJax

AIMv2 is a series of vision models pretrained with multimodal autoregressive objectives, demonstrating excellent performance across multiple benchmarks.

Computer VisionJax

AIMv2 is a series of vision models based on multimodal autoregressive objective pretraining, excelling in multiple benchmarks

Computer VisionJax

AIMv2 is a series of vision models pretrained with multimodal autoregressive objectives, achieving excellent performance across multiple multimodal understanding benchmarks.

Computer VisionJax

AIMv2 is a series of vision models pretrained with multimodal autoregressive objectives, achieving outstanding performance in multiple multimodal understanding benchmarks.

Computer VisionJax

AIMv2 is a series of vision models pretrained with multimodal autoregressive objectives, achieving outstanding performance across multiple visual understanding benchmarks.

Computer VisionJax

AIMv2 is a series of vision models based on multimodal autoregressive objective pretraining, excelling in various vision tasks.

Computer VisionJax