Dataset Viewer
The dataset viewer is not available for this subset.
Cannot get the split names for the config 'default' of the dataset.
Exception:    SplitsNotFoundError
Message:      The split names could not be parsed from the dataset config.
Traceback:    Traceback (most recent call last):
                File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/json/json.py", line 290, in _generate_tables
                  pa_table = paj.read_json(
                      io.BytesIO(batch), read_options=paj.ReadOptions(block_size=block_size)
                  )
                File "pyarrow/_json.pyx", line 342, in pyarrow._json.read_json
                File "pyarrow/error.pxi", line 155, in pyarrow.lib.pyarrow_internal_check_status
                  return check_status(status)
                File "pyarrow/error.pxi", line 92, in pyarrow.lib.check_status
                  raise convert_status(status)
              pyarrow.lib.ArrowInvalid: JSON parse error: Column(/5/inputs/clip/[]) changed from string to number in row 0
              
              During handling of the above exception, another exception occurred:
              
              Traceback (most recent call last):
                File "/usr/local/lib/python3.14/site-packages/datasets/inspect.py", line 286, in get_dataset_config_info
                  for split_generator in builder._split_generators(
                                         ~~~~~~~~~~~~~~~~~~~~~~~~~^
                      StreamingDownloadManager(base_path=builder.base_path, download_config=download_config)
                      ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                  )
                  ^
                File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/json/json.py", line 101, in _split_generators
                  pa_table = next(iter(self._generate_tables(**splits[0].gen_kwargs, allow_full_read=False)))[1]
                             ~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/json/json.py", line 304, in _generate_tables
                  batch = json_encode_fields_in_json_lines(original_batch, json_field_paths)
                File "/usr/local/lib/python3.14/site-packages/datasets/utils/json.py", line 111, in json_encode_fields_in_json_lines
                  examples = [ujson_loads(line) for line in original_batch.splitlines()]
                              ~~~~~~~~~~~^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/utils/json.py", line 20, in ujson_loads
                  return pd.io.json.ujson_loads(*args, **kwargs)
                         ~~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^
              ValueError: Expected object or value
              
              The above exception was the direct cause of the following exception:
              
              Traceback (most recent call last):
                File "/src/services/worker/src/worker/job_runners/config/split_names.py", line 71, in compute_split_names_from_streaming_response
                  for split in get_dataset_split_names(
                               ~~~~~~~~~~~~~~~~~~~~~~~^
                      path=dataset,
                      ^^^^^^^^^^^^^
                      config_name=config,
                      ^^^^^^^^^^^^^^^^^^^
                      token=hf_token,
                      ^^^^^^^^^^^^^^^
                  )
                  ^
                File "/usr/local/lib/python3.14/site-packages/datasets/inspect.py", line 340, in get_dataset_split_names
                  info = get_dataset_config_info(
                      path,
                  ...<6 lines>...
                      **config_kwargs,
                  )
                File "/usr/local/lib/python3.14/site-packages/datasets/inspect.py", line 291, in get_dataset_config_info
                  raise SplitsNotFoundError("The split names could not be parsed from the dataset config.") from err
              datasets.inspect.SplitsNotFoundError: The split names could not be parsed from the dataset config.

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.

Production ComfyUI workflows, API format

38 ComfyUI workflows in API format (the shape /prompt accepts, not the editor's save format). These are not demos — they are the graphs behind the image tools on prathom.ai, running against a single RTX 4080.

Everything here was debugged against real images. The notes below describe bugs that were live in production and are easy to reproduce if you build the same graphs yourself. That is the part worth reading.

The four bugs, and what they look like

1. Background removal produces an inverted alpha

RemoveBackground (BiRefNet) returns a mask where the subject is 0 and the background is 1. JoinImageWithAlpha wants the opposite. Wire them directly and you get a transparent PNG of the background, with the subject cut out — the exact inverse of the request. It looks plausible in a thumbnail, which is why it survives review.

InvertMask between them fixes it. See transparent-png.json, node 4.

This applies to JoinImageWithAlpha only. ImageCompositeMasked takes the mask the other way round, so product-background.json and white-background.json correctly have no InvertMask — adding one "for consistency" breaks them. The polarity is a property of the consuming node, not of the mask.

2. Qwen-Image-Edit silently forces square output

EmptySD3LatentImage with literal width/height sets the output size regardless of the input. A 1920×1080 photo through a graph with a hardcoded 1024×1024 latent comes back square and stretched.

Two nodes fix it:

ImageScaleToTotalPixels(megapixels=1.0, resolution_steps=16)
        ↓
GetImageSize  →  EmptySD3LatentImage.width / .height

resolution_steps: 16 matters — latent dimensions must be a multiple of 16 or the sampler pads and you lose a strip of the image. See any of the 13 edit workflows, e.g. anime-converter.json, nodes 12 and 13.

Deliberately not applied to the 10 fixed-format workflows. linkedin-banner (1584×396), x-header (1500×500), youtube-thumbnail-generator (1280×720) and the rest must emit their platform's exact dimensions. Deriving size from the input would break the one thing those graphs exist to do.

3. A hardcoded seed means the retry button does nothing

Every generative workflow started with a literal seed. Someone who disliked their cartoon and pressed the button again received a byte-for-byte identical image, with nothing on the page to explain why.

The 20 generative workflows here use "seed": "{{seed}}", and the caller substitutes a fresh random value per submission.

Four keep a literal seed on purpose: remove-scratches, remove-dust, remove-noise, ai-face-restore. Those are restoration passes, where two runs disagreeing about the same physical damage is a defect rather than a feature. If you would rather re-roll a restoration, change them — the trade-off is real and it goes both ways.

4. Compositing onto a fixed canvas ignores the source dimensions

ImageCompositeMasked with resize_source: true and a fixed EmptyImage canvas scales the subject to the canvas rather than placing it on it. Portraits come back squashed.

white-background.json takes the canvas from GetImageSize on the input and sets resize_source: false. ai-passport-photo.json is the fuller version: image and mask are scaled separately — lanczos for the image, bilinear for the mask, because a sharpening filter on a mask produces ringing at the cut edge — then recombined through ImageToMask.

Placeholders

These are templates. Substitute before POSTing to /prompt:

Placeholder Meaning
{{input}} filename returned by /upload/image
{{seed}} fresh random int per submission
{{preset}} rescale factor. RealESRGAN emits 4x, so 2x → 0.5, 4x → 1
{{instruction}} the edit prompt, for the Qwen graphs
{{passportWidth}}, {{passportHeight}} target size in pixels

Model filenames are literal and will need changing to match your models/ directory.

Models referenced

qwen_image_edit_2509_fp8_e4m3fn.safetensors    23 workflows
qwen_2.5_vl_7b_fp8_scaled.safetensors          23
qwen_image_vae.safetensors                     23
birefnet.safetensors                            5
RealESRGAN_x4plus.pth                           5
ddcolor_paper.pth                               2
RealVisXL_V5.0_fp16.safetensors                 1
bbox/face_yolov8m.pt                            1

Tested on ComfyUI 0.30.1 / torch 2.12.1+cu130, RTX 4080 16 GB. The Qwen fp8 graphs fit in 16 GB at 1 MP; they do not at 2 MP.

One operational note

If you run several of these back to back, check free VRAM after unloading rather than before. Reading it once and refusing on a stale number rejects a graph for a shortage that a /free call would have cleared. It presents as an out-of-memory error while the GPU sits idle, and it is easy to mistake for a hardware limit.

Licence

Apache-2.0, for the workflows. prathom.ai itself is not open source.

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