Dataset Viewer
Duplicate
The dataset viewer is not available for this split.
Cannot extract the features (columns) for the split 'train' of the config 'default' of the dataset.
Error code:   FeaturesError
Exception:    ArrowInvalid
Message:      Schema at index 1 was different: 
_class_name: string
_diffusers_version: string
_name_or_path: string
feature_extractor: list<item: null>
requires_safety_checker: null
safety_checker: list<item: null>
scheduler: list<item: string>
text_encoder: list<item: string>
tokenizer: list<item: string>
unet: list<item: string>
vae: list<item: string>
vs
_class_name: string
_diffusers_version: string
algorithm_type: string
beta_end: double
beta_schedule: string
beta_start: double
clip_sample: bool
clip_sample_range: double
dynamic_thresholding_ratio: double
lower_order_final: bool
num_train_timesteps: int64
prediction_type: string
sample_max_value: double
set_alpha_to_one: bool
solver_order: int64
solver_type: string
steps_offset: int64
thresholding: bool
timestep_spacing: string
trained_betas: null
use_karras_sigmas: bool
Traceback:    Traceback (most recent call last):
                File "/src/services/worker/src/worker/job_runners/split/first_rows.py", line 243, in compute_first_rows_from_streaming_response
                  iterable_dataset = iterable_dataset._resolve_features()
                                     ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 3496, in _resolve_features
                  features = _infer_features_from_batch(self.with_format(None)._head())
                                                        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 2257, in _head
                  return next(iter(self.iter(batch_size=n)))
                         ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 2461, in iter
                  for key, example in iterator:
                                      ^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 1952, in __iter__
                  for key, pa_table in self._iter_arrow():
                                       ^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 1974, in _iter_arrow
                  yield from self.ex_iterable._iter_arrow()
                File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 531, in _iter_arrow
                  yield new_key, pa.Table.from_batches(chunks_buffer)
                                 ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "pyarrow/table.pxi", line 5039, in pyarrow.lib.Table.from_batches
                File "pyarrow/error.pxi", line 155, in pyarrow.lib.pyarrow_internal_check_status
                File "pyarrow/error.pxi", line 92, in pyarrow.lib.check_status
              pyarrow.lib.ArrowInvalid: Schema at index 1 was different: 
              _class_name: string
              _diffusers_version: string
              _name_or_path: string
              feature_extractor: list<item: null>
              requires_safety_checker: null
              safety_checker: list<item: null>
              scheduler: list<item: string>
              text_encoder: list<item: string>
              tokenizer: list<item: string>
              unet: list<item: string>
              vae: list<item: string>
              vs
              _class_name: string
              _diffusers_version: string
              algorithm_type: string
              beta_end: double
              beta_schedule: string
              beta_start: double
              clip_sample: bool
              clip_sample_range: double
              dynamic_thresholding_ratio: double
              lower_order_final: bool
              num_train_timesteps: int64
              prediction_type: string
              sample_max_value: double
              set_alpha_to_one: bool
              solver_order: int64
              solver_type: string
              steps_offset: int64
              thresholding: bool
              timestep_spacing: string
              trained_betas: null
              use_karras_sigmas: bool

Need help to make the dataset viewer work? Make sure to review how to configure the dataset viewer, and open a discussion for direct support.

SD1.5_rknn_3588_euler (Assets)

This repository contains pre-converted binary assets for running Stable Diffusion 1.5 (Euler) on Rockchip RK3588 / RK3588S using RKNN.

⚠️ Important
This is NOT a Hugging Face “model” intended for from_pretrained().
It is a DATASET that stores hardware-specific binaries (.rknn) and weights.

The runtime, CLI, and WebUI are hosted separately on GitHub.


What this repository contains

. ├── models/ │ └── business_rknn/ │ ├── unet/ # SD1.5 UNet (Realistic Vision–based) │ │ └── model.rknn │ ├── text_encoder/ │ ├── vae_encoder/ │ ├── vae_decoder/ │ └── scheduler/ │ ├── model/ │ └── sr/ │ └── realesrgan/ │ └── realesrgan_x4plus_tile128_fp16.rknn │ └── gfpgan/ └── weights/ ├── GFPGANv1.4.pth ├── detection_Resnet50_Final.pth └── parsing_parsenet.pth


Model details

  • Base architecture: Stable Diffusion 1.5
  • Primary checkpoint: Realistic Vision (SD1.5)
  • Scheduler: Euler
  • Runtime format: RKNN
  • Target hardware: Rockchip RK3588 / RK3588S

Super-Resolution

  • Real-ESRGAN x4 (RKNN)
  • ⚠️ Upscaling is limited to ×4 only
    (this is a model limitation, not configurable)

Intended usage

These assets are meant to be downloaded explicitly by a custom runtime.

Typical usage pattern:

  • Clone runtime code from GitHub
  • Download this dataset via huggingface_hub.snapshot_download()
  • Place files into expected directories
  • Run inference using RKNN

➡️ Runtime & usage instructions:
GitHub: https://github.com/Mojo24x7/SD1.5_rknn_3588_euler


License & credits

  • All model weights are provided under their original upstream licenses
  • This repository does not claim ownership of:
    • Stable Diffusion
    • Realistic Vision
    • Real-ESRGAN
    • GFPGAN

See the GitHub repository for full credits and acknowledgements.


Disclaimer

This dataset is provided for research, experimentation, and personal use.
The author is not affiliated with Stability AI, CompVis, Rockchip, or Hugging Face.

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