The top 5 hugging face models & datasets measured by RiseFinder over the 1d window ending 4 October 2026.
Mitsuba-ComfyUI-27B-GGUF is a text generation model distributed in GGUF format on Hugging Face. It is a ternary (1.58-bit) quantized version of Qwen3.8-27B, tuned for use with ComfyUI. Its stated purpose is writing image and video generation prompts that follow strict conditions, and describing images.
Hugging Face model
Open source ↗biglam/europeana_newspapers_images is a dataset of 98,877 newspaper page images from the 1700s to the 1940s in 10 languages, plus pages marked multi-language or unidentified. Each page is paired with the OCR produced when it was digitised, including full text, ALTO XML, and line and word boxes converted to image pixels with the OCR engine's per-word confidence values.
Hugging Face dataset
Open source ↗GLiNER2.5-Decide is a 340M-parameter English text classification model in the GLiNER2.5 family. Instead of using a fixed prompt template, it accepts any label set at call time, covering uses such as intent, routing, sentiment, priority, policy, and multi-label tagging, all in a single forward pass without generating tokens. It can be loaded with AutoExtractor and run locally.
Hugging Face model
Open source ↗Julia 1 is a machine learning model from SupersonicLabs and the first model in its Julia family. It is a small model of 144.3M parameters that takes a state, a question, and possible answers as input and produces a single decision. The same interface supports classification, routing, ordered scores, and Boolean decisions.
Hugging Face model
Open source ↗fastino/fast-decisions is a classification dataset suite associated with GLiNER2.5-Decide. It covers seventeen domains, with one file per domain. Each row contains a document plus the decisions a product has to make, including the task name, the candidate labels, and the gold label. The suite includes both single-label heads, which have one gold string, and multi-label heads.
Hugging Face dataset
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