This is a quantized version of the Microsoft Fara-7B model, optimized using the imatrix technology of llama.cpp. The model supports multiple quantization levels, from high-precision bf16 to extremely low-precision IQ2_M, meeting the needs of different hardware configurations and performance requirements.

Natural Language ProcessingGguf

This is the GGUF quantized version of the ai-sage/GigaChat3-10B-A1.8B-bf16 model, offering a variety of quantization options, from high-precision Q8_0 to extremely compressed smol-IQ1_KT, to meet the deployment requirements under different hardware conditions. This model supports a 32K context length, adopts the MLA architecture, and is optimized for dialogue scenarios.

Natural Language ProcessingGgufOther

The Brazilian scope routing model is a fine-tuned micro large language model based on Gemma 3 270M, specifically designed for the Brazilian food delivery service system. It can serve as an extremely fast and lightweight intent classifier (router). This model is trained using Unsloth and converted to the GGUF format.

Natural Language ProcessingSafetensorsOther

Chronos-2 is a time series foundation model with 120 million parameters, supporting zero-shot prediction. It supports univariate, multivariate, and covariate-aware tasks within a single architecture, achieving state-of-the-art accuracy in zero-shot prediction across multiple benchmarks, and has extremely high inference efficiency.

Scientific ComputingSafetensors

This is a LoRA fine-tuned model based on Qwen-Image-Edit-2509, specifically designed for the image fusion task of converting white background images to specific scenes, and performs extremely well.

Computer VisionDiffusers

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

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

This is a quantized version of the Microsoft UserLM-8b model, using the imatrix quantization technology of llama.cpp. It can significantly reduce memory usage and improve inference speed while maintaining model performance. It supports multiple quantization levels, from high quality to extreme compression, suitable for different hardware environments.

Natural Language ProcessingGguf

Qwen3-Next-80B-A3B-Instruct is an efficient sparse mixture of experts model developed by the Tongyi Qianwen team. It has a total of 80 billion parameters, with only 3 billion active parameters. The model adopts an innovative hybrid attention mechanism and a MoE architecture with an extremely low activation rate, significantly improving inference efficiency while maintaining strong performance. It natively supports a context length of 262,000 tokens and can be extended to 1 million tokens.

Natural Language ProcessingTransformers

Qwen3-Next-80B-A3B-Instruct-q2-mlx is an extremely quantized version in MLX format converted from the Qwen3-Next-80B-A3B-Instruct model, mainly used for text generation tasks. This version uses q2 quantization, and the model size is approximately 23GB. As a proof-of-concept version, there may be repetition and hallucination issues.

Natural Language ProcessingMlx

MiniCPM4.1-8B GGUF is an efficient large language model designed specifically for edge devices. It has carried out systematic innovations in four key dimensions: model architecture, training data, training algorithm, and inference system, achieving extreme efficiency improvement. It supports a context length of 65,536 tokens and a hybrid inference mode.

Natural Language ProcessingTransformersMultiple Languages

This is the Llamacpp imatrix quantization version of the NVIDIA Nemotron-Nano-12B-v2 model, offering a variety of quantization options, from BF16 to IQ2 quantization with extremely low bit rates, to help users run the model efficiently under different hardware conditions.

Natural Language ProcessingGguf

This is a quantized version of the NVIDIA Nemotron-H-47B-Reasoning-128K model, optimized using the imatrix technology of llama.cpp. The model supports a context length of 128K and is designed for reasoning tasks. It offers a variety of quantization options from BF16 to extremely low bitrates, suitable for different hardware configurations and performance requirements.

Natural Language ProcessingGguf

This is a quantized version of the DeepSeek-V3.1 model, which uses the imatrix technology of llama.cpp for quantization processing. The aim is to improve the operating efficiency and performance of the model on different hardware. This version offers multiple quantization levels, ranging from high-quality Q8_0 to extremely low-quality IQ1_M, to meet the requirements of different hardware configurations and performance needs.

Natural Language ProcessingGguf

This is a quantized version of the EXAONE-4.0.1-32B model of LGAI-EXAONE, processed by the imatrix quantization technology of llama.cpp, which can run efficiently under different hardware conditions. It provides a variety of quantization options from BF16 to extremely low bit rates, suitable for various memory and performance requirements.

Natural Language ProcessingGguf

Tiny GptOssForCausalLM is a minimized causal language model designed specifically for unit tests of the TRL (Transformer Reinforcement Learning) library. This model is extremely small in scale and is mainly used to verify the correctness of the operation of reinforcement learning-related functions in the TRL library under a specific model architecture.

Natural Language ProcessingTransformers

This is the GGUF quantized version of Tencent Hunyuan's 0.5B instruction fine-tuning model. It is quantized using the imatrix technology of llama.cpp, offering multiple quantization options from BF16 to extremely low bit rates, suitable for Chinese dialogue tasks in resource-constrained environments.

Natural Language ProcessingGguf

The A3ON-1B Quantized Model is a multi-quantized version based on the kaiiddo/A3ON-1B base model, specifically optimized for text generation and code assistance scenarios. It offers different quantization options from extremely low bitrates to high quality, suitable for resource-constrained environments and high-precision requirement scenarios.

Natural Language ProcessingTransformersEnglish

This is a coding/programming model based on the Qwen 3 platform, with complete reasoning ability and extremely fast speed. It can process more than 150 tokens per second on medium hardware and more than 50 tokens per second even when using only the CPU. It is a general-purpose coding model suitable for generating code blocks, ideating coding ideas, and quickly generating code drafts.

Natural Language ProcessingGgufMultiple Languages

An advanced Transformer model that has been carefully fine-tuned, specifically designed for species entity recognition. It can accurately identify species names from the Species-800 dataset and has extremely high accuracy and reliability in clinical and research applications.

Natural Language ProcessingTransformersEnglish