datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
sponsorblock-youtube-metadata-2024
SponsorBlock YouTube Metadata Dataset
A dataset of YouTube video metadata collected from a subset of videos in the SponsorBlock database. This dataset contains metadata, subtitles, engagement heatmaps, live chat, and channel playlist information for popular YouTube videos.
Contains the top videos from the SponsorBlock database that had data added in the year 2024.
Quick Stats
Metric
Value
Total videos
154,536
Videos with subtitles
62,819 (41%)… See the full description on the dataset page: https://huggingface.co/datasets/ScriptSmith/sponsorblock-youtube-metadata-2024.upvoteweb-posts
upvoteweb: posts
Posts in upvoteweb.
configs
[!IMPORTANT]There are several configs representing different permutations of this dataset. Load the relevant config for the task you are interested in.
Overview of configs:
default: largely unfiltered/unprocessed original data
eduscored: the "eduscore" predicted on the text column with huggingface's trained classifier
en-clean: filter language for en and language_score for > 0.6. Run clean-text on the text col, preserving… See the full description on the dataset page: https://huggingface.co/datasets/BEE-spoke-data/upvoteweb-posts.qwen3.5-2b-base-blind-spots
Qwen3.5-2B-Base — Blind Spot Analysis (Text + Vision)
Model Tested
Field
Value
Model
Qwen/Qwen3.5-2B-Base
Parameters
2.27 B (2,274 M per HF metadata)
Architecture
Hybrid Gated-DeltaNet (dense FFN) — 24 LM layers (18 DeltaNet + 6 full-attention), ViT vision encoder
Type
Pre-trained base model (not instruction-tuned)
Context
262 144 tokens
Modalities
Text + Vision (early-fusion multimodal)
Key Contributions
Only multimodal… See the full description on the dataset page: https://huggingface.co/datasets/F555/qwen3.5-2b-base-blind-spots.SpotAgenticCoT
SpotAgenticCoT: Agentic Trajectories for Visual Geo-localization
Project Page
Dataset Description
SpotAgenticCoT (specifically referring to the SpotAgenticCoT-6k subset described in the paper) is a high-quality dataset of ~6,000 agentic reasoning trajectories designed for visual geo-localization tasks.
Unlike traditional geo-localization datasets that only provide image-coordinate pairs, SpotAgenticCoT contains full ReAct (Reasoning + Acting) traces. Each sample… See the full description on the dataset page: https://huggingface.co/datasets/jiafr1802/SpotAgenticCoT.