The top 5 Hugging Face models and datasets by download growth over the 1-day window ending 5 November 2026, measured by RiseFinder.
| Rank | Name | Before → after | Change |
|---|---|---|---|
| 1 | TacVerse/TacVerse | 539 → 796 downloads | +47.7% |
| 2 | Vyber07/cyber-security | 9,588 → 10,815 downloads | +12.8% |
| 3 | LiquidAI/LFM3-Omni-2B | 11,662 → 13,057 downloads | +12% |
| 4 | Diffuspace/Clover-35B-A3B-Preview | 3,017 → 3,341 downloads | +10.7% |
| 5 | bitmanagerai-speech-lab/darbuka_arabic_tts_dataset | 1,507 → 1,651 downloads | +9.6% |
TacVerse is a large-scale dataset for bimanual manipulation research in which every frame carries four streams of high-resolution visuotactile sensing, two per gripper, alongside synchronized camera views. It was collected with a handheld UMI gripper pair carrying Xense Neutron visuotactile sensors across three real-world scene families: office, home, and workbench.
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 ↗LiquidAI/LFM3-Omni-2B is an AI model that handles multiple kinds of input and output in a single system. It understands text, images, video and audio, and responds in text or speech. It is built for on-device use, replacing what would otherwise require a separate ASR model, vision-language model, LLM and TTS model.
Hugging Face model
Open source ↗Clover-35B-A3B-Preview is a diffusion language model and the first model released by DiffuSpace. It combines a 35B-parameter mixture-of-experts backbone with approximately 3B active parameters. At release, it delivered state-of-the-art performance among open-source diffusion language models on the benchmarks reported in the launch blog.
Hugging Face model
Open source ↗This dataset is intended for research in the fields of speech recognition and text-to-speech applications. It compiles Arabic speech samples along with their corresponding automatic transcripts and audio-quality measurements. The data collection has a specific focus on capturing speech patterns from Egyptian and Saudi speakers.
Hugging Face dataset
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