The top 5 hugging face models & datasets measured by RiseFinder over the 1d window ending 17 October 2026.
MiniCPM-V 4.7 is a vision-language model from the MiniCPM-V series, released in a 1B variant. It handles single-image, multi-image, and video understanding, and combines foundation capabilities with efficient visual encoding and on-device inference, meaning it can run on local devices rather than only in the cloud.
Hugging Face model
Open source ↗vllm-sr/d3 is a 27B multimodal foundation decision model, part of Decision 3.0, the decision models of vLLM Semantic Router. It takes an input in text or JSON form, optionally with images and videos, together with questions to answer. It can pick one of several options, say yes or no, or rate on a scale, and answers all of the questions it is given.
Hugging Face model
Open source ↗EgoStandard is a video dataset from LightwheelAI. It is described as the 90,000-hour head-view line of EgoSuite-Open100K. The dataset pairs head-view egocentric video with synchronized 3D hand pose, and its body subset adds full-body pose. It is distributed through the LightwheelAI/EgoStandard Bucket, with a Git repository serving as the dataset card and access point for downloads.
Hugging Face dataset
Open source ↗Vyber07/cyber-security is a cybersecurity knowledge base dataset intended for AI training. It covers cybersecurity domains including offensive red teaming, bug bounty exploitation, defensive SOC operations, digital forensics, and AI/LLM security. The dataset is 16 GB in size, contains 507 files, and spans more than 30 domains drawn from more than 15 platforms.
Hugging Face dataset
Open source ↗d3-flash is a 9B multimodal foundation decision model that is part of Decision 3.0, the decision models of vLLM Semantic Router. It accepts text or JSON input, optionally with images and videos, along with a question to answer. It is built for structured decision tasks such as picking one of several options, answering yes or no, or rating on a scale.
Hugging Face model
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