The top 4 hugging face models & datasets measured by RiseFinder over the 1d window ending 18 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 ↗This is a machine learning dataset containing a selected code corpus of approximately 240 billion tokens covering 11 programming languages from The Stack v3. The data was produced through quality-control cleaning and fine-grained selection using the UltraData-Code-L2-Classifier, applying a language-adaptive L2 selection framework.
Hugging Face dataset
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 ↗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
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