This is a GGUF format version converted from the Qwen3-VL-30B-A3B-Instruct model, specifically optimized for llama.cpp. This model is a multimodal visual language model with 30 billion parameters, supporting image understanding and text generation tasks.

MultimodalGguf

This is a GGUF format version converted from the Qwen/Qwen3-4B-Thinking-2507 model, using Q8_0 quantization, which can be used compatibly with llama.cpp. This model has chain-of-thought reasoning ability and has 4 billion parameters.

Natural Language ProcessingTransformers

embeddinggemma-300m-qat-q8_0 GGUF is a quantized version based on the Google embeddinggemma-300m model, specifically designed for feature extraction and sentence similarity calculation. This model has been quantized and optimized to significantly reduce the model size and inference overhead while maintaining high accuracy.

Natural Language ProcessingSentence-transformers

embeddinggemma-300M is a lightweight text embedding model optimized through quantization. Based on Google's embeddinggemma architecture, it uses QAT (Quantization-Aware Training) and Q4_0 quantization techniques, with 300M parameters. This model is specifically designed to generate high-quality text embedding vectors and supports tasks such as sentence similarity calculation and feature extraction.

Natural Language ProcessingSentence-transformers

Qwen2.5-Omni-7B-GGUF is the GGUF format version of the Qwen2.5-Omni-7B model, supporting multimodal inputs including text, audio, and images.

MultimodalGgufEnglish

Qwen2.5-Omni-3B is a multimodal model that supports text, audio, and image input, but does not support video input or audio generation.

MultimodalGgufEnglish

Ultravox v0.5 is an audio-to-text model optimized from the Llama-3 2.1B architecture, focusing on efficient speech transcription tasks.

Audio ProcessingGguf

This is a vision-enhanced version based on Mistral-Small-3.1-24B-Instruct-2503, supporting image-to-text generation tasks.

MultimodalGguf

Nomic Embed Text V2 GGUF is a multilingual text embedding model supporting over 70 languages, suitable for sentence similarity calculation and feature extraction tasks.

Natural Language ProcessingGgufMultiple Languages

This project provides a quantized version of the Qwen/Qwen3-14B model in the GGUF format, supporting various quantization levels (2-bit to 8-bit), facilitating efficient deployment and operation on various hardware. GGUF is an alternative format to GGML and is supported by multiple mainstream clients and libraries.

Natural Language ProcessingGguf

This is the GGUF format quantized version of the Qwen/Qwen3-8B model, quantized by MaziyarPanahi. GGUF is a new format introduced by the llama.cpp team, replacing the no-longer-supported GGML format. It supports various quantization levels (2-bit to 8-bit), facilitating efficient operation on various hardware.

Natural Language ProcessingGguf

This is the GGUF format version of the Qwen/Qwen3-1.7B model, quantized by MaziyarPanahi. GGUF is a new format developed by the llama.cpp team to replace the GGML format. It supports various quantization levels (from 2-bit to 8-bit), facilitating deployment and operation on various hardware.

Natural Language ProcessingGguf

This model is converted from BAAI/bge-reranker-v2-m3 into GGUF format using llama.cpp via ggml.ai's GGUF-my-repo space, primarily for text classification tasks.

Natural Language ProcessingGgufOther

Gemma 3 is a lightweight multimodal model launched by Google. It is built on the same technology as Gemini, supports text and image inputs, and outputs text. It is suitable for various tasks.

MultimodalGguf

Gemma 3 is a lightweight open-source multimodal model series launched by Google, built on the same technology as Gemini, supporting text and image inputs and generating text outputs

MultimodalGguf

Gemma 3 is a lightweight open-source multimodal model from Google, supporting text and image inputs with text outputs, featuring a 128K context window and support for 140+ languages.

MultimodalGguf

This model is a quantized version converted from google-t5/t5-small to GGUF format using llama.cpp via ggml.ai's GGUF-my-repo space.

Natural Language ProcessingGgufMultiple Languages

This model was converted from HKUSTAudio/Llasa-8B to GGUF format using llama.cpp via ggml.ai's GGUF-my-repo space, designed for text-to-speech tasks.

Audio ProcessingGgufMultiple Languages

GTE-small is an efficient sentence embedding model based on the thenlper/gte-small foundation model, focusing on sentence similarity tasks.

Natural Language ProcessingGgufEnglish

This is a GGUF format model converted from the Qwen2.5-Coder-0.5B model, suitable for code generation tasks.

Natural Language ProcessingGgufMultiple Languages