Qwen2.5 is a new-generation large language model launched by Alibaba. It has made important optimizations in the chat template, permanently disabled the thinking state, solved problems related to the multi-round chat template, and provided a more convenient experience for experiments and research.

Natural Language ProcessingTransformers

This is the MXFP4_MOE quantized version of the MiniMax-M2 model. It is re-quantized based on the version with the chat template fixed by unsloth, enabling more efficient use of the MiniMax-M2 model's capabilities in specific scenarios. This is a coding model that needs to be used with the latest llama.cpp.

Natural Language ProcessingGguf

Lamapi/next-12b is a multilingual large language model with 12 billion parameters, offering multiple quantized versions and supporting various natural language processing tasks such as text generation, question answering, and chatting. This model is trained on multiple domain datasets and features high efficiency and lightweight characteristics.

Natural Language ProcessingTransformersMultiple Languages

nanochat-d32 is a lightweight chat model specifically optimized for the ONNX runtime, providing efficient text generation capabilities. This model is converted from karpathy's nanochat-d32 model and supports running in a JavaScript environment.

Natural Language ProcessingTransformers

Qwen3-VL-8B-Thinking-MNN is a 4-bit quantized version of the MNN model exported from Qwen3-VL-8B-Thinking, optimized for text generation and chat scenarios, and supports visual language understanding tasks.

xLSTM-7b-Instruct is an experimental fine-tuned version based on NX-AI/xLSTM-7b, specifically optimized for instruction-following tasks. This model adds support for chat templates and uses TRL for supervised fine-tuning training, aiming to provide a better conversational interaction experience.

Natural Language ProcessingTransformers

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

NVIDIA GPT-OSS-120B Eagle3 is an optimized version based on the OpenAI gpt-oss-120b model. It adopts the Mixture of Experts (MoE) architecture, with a total of 120 billion parameters and 5 billion active parameters. This model supports both commercial and non-commercial use and is suitable for text generation tasks, especially for the development of AI Agent systems, chatbots, and other applications.

Natural Language ProcessingSafetensors

Granite-4.0-H-Micro is a 3-billion parameter long-context instruction model developed by IBM, fine-tuned from Granite-4.0-H-Micro-Base. This model combines open-source instruction datasets and internal synthetic datasets, and is developed using techniques such as supervised fine-tuning, reinforcement learning alignment, and model merging. It has a structured chat format and performs excellently in instruction following and tool invocation capabilities.

Natural Language ProcessingTransformers

OpenLLaMA 3B v2 is an open-source large language model based on the Transformer architecture, with 3 billion parameters. This model uses the MIT license and is mainly used for English text generation tasks, supporting various application scenarios such as chatbots.

Natural Language ProcessingPeftEnglish

This project is a text generation model obtained by quantizing the Qwen3-4B model using AMD's quantization tool. It can be used in scenarios such as chatting. The model is prepared using the AMD Quark quantization tool and undergoes necessary post-processing.

Natural Language ProcessingOnnxEnglish

Qwen2.5-14B-Instruct is a large language model with 14 billion parameters, designed specifically for chat and text generation scenarios. This model is built based on the transformers library and is suitable for internal testing and lightweight application deployment.

Natural Language ProcessingTransformersEnglish

MEDFIT-LLM-3B is a language model specifically optimized for medical Q&A, fine-tuned based on Meta's Llama-3.2-3B-Instruct. This model is trained on medical datasets using LoRA technology, significantly improving its understanding and direct answering abilities in the medical field. It is suitable for applications such as medical chatbots and patient education.

Natural Language ProcessingTransformersEnglish

A search query generation model fine-tuned based on the Qwen3 0.6B model, capable of generating relevant search queries based on user input and conversation context, suitable for application scenarios such as search engine suggestion systems and chatbots.

Natural Language ProcessingTransformersEnglish

NVIDIA Nemotron Nano 9B v2 is a high-performance large language model developed by NVIDIA. It adopts the Mamba2-Transformer hybrid architecture, supports multilingual inference and chat tasks, and performs excellently in multiple benchmark tests. It especially supports the runtime 'thinking' budget control function.

Natural Language ProcessingTransformersMultiple Languages

The NVIDIA Qwen3-32B FP4 model is a quantized version of Alibaba's Qwen3-32B model. It uses an optimized Transformer architecture and performs FP4 quantization on weights and activations. It is suitable for AI applications such as AI agent systems, chatbots, and RAG systems.

Natural Language ProcessingSafetensors

The NVIDIA Qwen3-14B FP4 model is a quantized version of Alibaba's Qwen3-14B model, optimized using the FP4 data type and enabling efficient inference through TensorRT-LLM. This model is specifically designed for NVIDIA GPU acceleration systems and is suitable for various AI application scenarios such as AI Agent systems, chatbots, and RAG systems. It supports both commercial and non-commercial use globally.

Natural Language ProcessingSafetensors

The NVIDIA Qwen3-8B FP4 model is a quantized version of Alibaba's Qwen3-8B model. It is an autoregressive language model with an optimized Transformer architecture. This model uses FP4 quantization technology, which significantly reduces memory usage and computational requirements while maintaining performance. It is suitable for applications such as AI agent systems, chatbots, and RAG systems.

Natural Language ProcessingSafetensors

This is a collection of quantized versions based on the huehui/Discord-Micae-Hermes-3-3B-abliterated model, providing GGUF files of various quantization types and sizes. This model is a 3B parameter dialogue model trained on the Discord-OpenMicae dataset, supporting dialogue interactions in ChatML format.

Natural Language ProcessingTransformersEnglish

This is the GGUF quantized version of the NVIDIA Nemotron Nano 12B v2 model, which uses a hybrid Mamba - 2 and Transformer architecture, supports multilingual inference and chat functions, has 12 billion parameters, and supports a context length of up to 128K.

Natural Language ProcessingTransformersMultiple Languages