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The docs attached show that datasets are a list of str. However this model with repo_id=Arch4ngel/pochita-plushie-v2 gives datasets of type str.
datasets
str
Arch4ngel/pochita-plushie-v2
from huggingface_hub import model_info
info = model_info(repo_id="Arch4ngel/pochita-plushie-v2", files_metadata=True)
ModelInfo(id='Arch4ngel/pochita-plushie-v2', author='Arch4ngel', sha='1ae5bf2e531bdd891a02cd51eb402af44d24ce6d', created_at=datetime.datetime(2022, 12, 29, 15, 18, 26, tzinfo=datetime.timezone.utc), last_modified=datetime.datetime(2023, 3, 16, 19, 41, 51, tzinfo=datetime.timezone.utc), private=False, disabled=False, downloads=26, downloads_all_time=None, gated=False, gguf=None, inference=None, likes=1, library_name='diffusers', tags=['diffusers', 'pytorch', 'stable-diffusion', 'text-to-image', 'diffusion-models-class', 'dreambooth-hackathon', 'wildcard', 'dataset:Arch4ngel/pochita_v2', 'license:creativeml-openrail-m', 'autotrain_compatible', 'endpoints_compatible', 'diffusers:StableDiffusionPipeline', 'region:us'], pipeline_tag='text-to-image', mask_token=None, card_data={'base_model': None, 'datasets': 'Arch4ngel/pochita_v2', 'eval_results': None, 'language': None, 'library_name': None, 'license': 'creativeml-openrail-m', 'license_name': None, 'license_link': None, 'metrics': None, 'model_name': None, 'pipeline_tag': None, 'tags': ['pytorch', 'diffusers', 'stable-diffusion', 'text-to-image', 'diffusion-models-class', 'dreambooth-hackathon', 'wildcard'], 'widget': [{'text': 'pochita plushie goes fishing'}]}, widget_data=[{'text': 'pochita plushie goes fishing'}], model_index=None, config={'diffusers': {'_class_name': 'StableDiffusionPipeline'}}, transformers_info=None, trending_score=None, siblings=[RepoSibling(rfilename='.gitattributes', size=1477, blob_id='c7d9f3332a950355d5a77d85000f05e6f45435ea', lfs=None), RepoSibling(rfilename='README.md', size=967, blob_id='a46199d1d25961b2a7f6afdffeafd91ca849bed0', lfs=None), RepoSibling(rfilename='feature_extractor/preprocessor_config.json', size=518, blob_id='0d9d33b883843d1b370da781f3943051067e1b2c', lfs=None), RepoSibling(rfilename='model_index.json', size=577, blob_id='86934934847de0105ac23a3d1bb3d2f2c911b1fe', lfs=None), RepoSibling(rfilename='safety_checker/config.json', size=4895, blob_id='bcfa996ef254bce2b6222ea224314a8c629e8eb4', lfs=None), RepoSibling(rfilename='safety_checker/pytorch_model.bin', size=1216064769, blob_id='c8835557a0d3af583cb06c7c154b7e54a069c41d', lfs=BlobLfsInfo(size=1216064769, sha256='16d28f2b37109f222cdc33620fdd262102ac32112be0352a7f77e9614b35a394', pointer_size=135)), RepoSibling(rfilename='scheduler/scheduler_config.json', size=317, blob_id='fe196bbd55e42e07581cc571347beda8bce89d45', lfs=None), RepoSibling(rfilename='text_encoder/config.json', size=612, blob_id='adf10c84a44fdfd1212940c5ada4716cbcb27bdc', lfs=None), RepoSibling(rfilename='text_encoder/pytorch_model.bin', size=492309793, blob_id='cd60c8e7580c7e9b0776e82aac6a689441c9e1b4', lfs=BlobLfsInfo(size=492309793, sha256='a20d724dacc3f94e73753462567b578a6395b725e17b4ddaeddf0dd3bc148729', pointer_size=134)), RepoSibling(rfilename='tokenizer/merges.txt', size=524619, blob_id='76e821f1b6f0a9709293c3b6b51ed90980b3166b', lfs=None), RepoSibling(rfilename='tokenizer/special_tokens_map.json', size=472, blob_id='2c2130b544c0c5a72d5d00da071ba130a9800fb2', lfs=None), RepoSibling(rfilename='tokenizer/tokenizer_config.json', size=806, blob_id='e67c855cfb2f0b62b11b07a593f20603c983c8d2', lfs=None), RepoSibling(rfilename='tokenizer/vocab.json', size=1059962, blob_id='469be27c5c010538f845f518c4f5e8574c78f7c8', lfs=None), RepoSibling(rfilename='unet/config.json', size=1068, blob_id='cad3da81355f76fba64ec4f8d166f8ef7592d345', lfs=None), RepoSibling(rfilename='unet/diffusion_pytorch_model.bin', size=3438375973, blob_id='16c830153a5eff07a27d204314bf099ba444382e', lfs=BlobLfsInfo(size=3438375973, sha256='a7982e038abeae13bf1d43e3d692c932f14040d9e982fb968352fefe0c491f42', pointer_size=135)), RepoSibling(rfilename='vae/config.json', size=629, blob_id='054aecb170d9bdd886c54f4abc3de925df9a8002', lfs=None), RepoSibling(rfilename='vae/diffusion_pytorch_model.bin', size=334715313, blob_id='a9b64f956a1741ccb1df1bc90916ad6131b7cab0', lfs=BlobLfsInfo(size=334715313, sha256='f3d17aa398e021a2600c4a8b570060056a069a1b7b6f8ace78ffa52fff69395d', pointer_size=134))], spaces=[], safetensors=None, security_repo_status=None)
- huggingface_hub version: 0.26.2 - Platform: macOS-15.0.1-arm64-arm-64bit - Python version: 3.11.7 - Running in iPython ?: No - Running in notebook ?: No - Running in Google Colab ?: No - Running in Google Colab Enterprise ?: No - Token path ?: /Users/adityaborikar/.cache/huggingface/token - Has saved token ?: False - Configured git credential helpers: osxkeychain - FastAI: N/A - Tensorflow: N/A - Torch: N/A - Jinja2: N/A - Graphviz: N/A - keras: N/A - Pydot: N/A - Pillow: N/A - hf_transfer: N/A - gradio: N/A - tensorboard: N/A - numpy: 1.26.4 - pydantic: N/A - aiohttp: N/A - ENDPOINT: https://huggingface.co - HF_HUB_CACHE: /Users/adityaborikar/.cache/huggingface/hub - HF_ASSETS_CACHE: /Users/adityaborikar/.cache/huggingface/assets - HF_TOKEN_PATH: /Users/adityaborikar/.cache/huggingface/token - HF_STORED_TOKENS_PATH: /Users/adityaborikar/.cache/huggingface/stored_tokens - HF_HUB_OFFLINE: False - HF_HUB_DISABLE_TELEMETRY: False - HF_HUB_DISABLE_PROGRESS_BARS: None - HF_HUB_DISABLE_SYMLINKS_WARNING: False - HF_HUB_DISABLE_EXPERIMENTAL_WARNING: False - HF_HUB_DISABLE_IMPLICIT_TOKEN: False - HF_HUB_ENABLE_HF_TRANSFER: False - HF_HUB_ETAG_TIMEOUT: 10 - HF_HUB_DOWNLOAD_TIMEOUT: 10
The text was updated successfully, but these errors were encountered:
ModelCardData
Hello @adiaholic, thanks a lot for reporting this! 🤗 I just opened a PR #2644 to fix the typing and align it with the API.
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Describe the bug
The docs attached show that
datasets
are a list ofstr
.However this model with repo_id=
Arch4ngel/pochita-plushie-v2
gives datasets of typestr
.Reproduction
from huggingface_hub import model_info
info = model_info(repo_id="Arch4ngel/pochita-plushie-v2", files_metadata=True)
Logs
System info
The text was updated successfully, but these errors were encountered: