ingu627

llama4-scout-q4

The Llama 4 collection of models are natively multimodal AI models that enable text and multimodal experiences. These models leverage a mixture-of-experts architecture to offer industry-leading performance in text and image understanding.

109b 400b

3,781 Pulls 3 Tags Updated 7 months ago

Qwen2.5-VL-7B-Instruct-Q5_K_M

Qwen2.5VL-7B-Instruct-Q5_K_M is a vision-language model from Alibaba Cloud with 7 billion parameters, designed for processing text and visual inputs, and optimized with Q5_K_M quantization for efficient deployment in ollama.

2,615 Pulls 1 Tag Updated 8 months ago

exaone4.0

The EXAONE 4.0 model series consists of two sizes: a mid-size 32B model optimized for high performance, and a small-size 1.2B model designed for on-device applications.

1.2b 32b

1,693 Pulls 3 Tags Updated 4 months ago

phi-4-mini-instruct-q4

Phi-4-mini-instruct is a lightweight open model built upon synthetic data and filtered publicly available websites - with a focus on high-quality, reasoning dense data. The model belongs to the Phi-4 model family and supports 128K token context length.

222 Pulls 1 Tag Updated 8 months ago

qwen3

Qwen3 is the latest generation of large language models in Qwen series, offering a comprehensive suite of dense and mixture-of-experts (MoE) models.

tools

72 Pulls 2 Tags Updated 7 months ago

EXAONE-Deep-7.8B

EXAONE Deep exhibits superior capabilities in various reasoning tasks including math and coding benchmarks released by LG AI Research.

45 Pulls 1 Tag Updated 8 months ago