The top 5 hugging face models & datasets measured by RiseFinder over the 1d window ending 3 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 ↗Anthropic/claude-protein-binder-design is a dataset of protein design experiment results. It contains 1,440 de novo miniprotein binders of 50 to 120 residues designed against 16 targets by two Claude models operating as autonomous protein-design agents, with wet-lab characterization from two contract research organizations. Each design includes binding calls and kinetics, structure predictions, and design provenance, and the tables join on a uuid column. Data and documentation are licensed CC BY 4.0.
Hugging Face dataset
Open source ↗IQuest-Q1 is a Mixture-of-Experts (MoE) language model developed by IQuest for agentic coding, reasoning, and multi-step tool use. It has approximately 320B total parameters with about 15B activated per token, exposes an OpenAI-compatible API, and can be deployed in production with SGLang or vLLM. The model accepts text-only input and its documentation notes that generated code and explanations can be incorrect and may require human oversight.
Hugging Face model
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
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