Download README.md from Axelless/3d-collection: direct link, hf CLI and curl.
- Browser
- Download file 2.26 kB
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https://huggingface.co/datasets/Axelless/3d-collection/resolve/main/README.md
- Command line
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hf download hf://datasets/Axelless/3d-collection/README.md
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curl -L -o README.md https://huggingface.co/datasets/Axelless/3d-collection/resolve/main/README.md
pretty_name: Scenario 3D Collection
license: cc-by-4.0
configs:
- config_name: default
data_files: data/*.parquet
Scenario 3D Collection
1,342 selected AI-generated 3D examples, with all 1,500 output files downloaded. About 39 GB including previews and available source inputs.
Another 393 examples made with Tencent Hunyuan models are published separately under their own licenses: Scenario 3D Collection (Hunyuan).
License
CC BY 4.0. Credit "Scenario". All assets are AI-generated.
Metadata
data/train-00000-of-00001.parquet is the single metadata source, with one row per example. Original assets remain separate files.
inputs: structured prompt, effort, generation settings and source assets (IDs, relative paths and SHA-256 hashes).outputs: structured output formats, roles, IDs, relative paths and SHA-256 hashes.preview: embedded thumbnail for the dataset viewer;preview_fileretains the original preview path and hash.input_filesandoutput_files: convenient download URLs. Top-level prompt and effort columns simplify browsing.
inputs.settings is JSON text because parameter names and value types vary between models; parse it with json.loads. All original parameter values and types are preserved. Missing values appear as null; no defaults are inferred. Paths are relative to the repository root.
Formats and validation
Outputs: 1,271 GLB, 137 Blender, 41 SPZ, 23 PLY, 21 VOX and 7 FBX. Structural checks passed; all 137 Blender outputs loaded with auto-execution disabled. One Blender scene references two missing textures. These checks do not certify rendering or animation quality.
Browse and download
import json
from datasets import load_dataset
examples = load_dataset("scenario-labs/3d-collection", split="train")
example = examples[0]
settings = json.loads(example["inputs"]["settings"] or "{}")
source_assets = example["inputs"]["assets"]
outputs = example["outputs"]
Use huggingface_hub.snapshot_download with repo_type="dataset" to download the original files. The Hunyuan companion requires access approval and authentication.