The dataset viewer is not available for this dataset.
Error code: ConfigNamesError
Exception: ImportError
Message: To be able to use axiong/pmc_oa, you need to install the following dependency: jsonlines.
Please install it using 'pip install jsonlines' for instance.
Traceback: Traceback (most recent call last):
File "/src/services/worker/src/worker/job_runners/dataset/config_names.py", line 66, in compute_config_names_response
config_names = get_dataset_config_names(
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/inspect.py", line 347, in get_dataset_config_names
dataset_module = dataset_module_factory(
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/load.py", line 1914, in dataset_module_factory
raise e1 from None
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/load.py", line 1880, in dataset_module_factory
return HubDatasetModuleFactoryWithScript(
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/load.py", line 1504, in get_module
local_imports = _download_additional_modules(
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/load.py", line 354, in _download_additional_modules
raise ImportError(
ImportError: To be able to use axiong/pmc_oa, you need to install the following dependency: jsonlines.
Please install it using 'pip install jsonlines' for instance.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.
PMC-OA Dataset
News: We have released the PMC-OA dataset. You can choose the subset specifically.
P.S. There's something wrong with the huggingface dataset viewer when the dataset scale gets large. So we sample a subset of it to visualize it directly on web. Click PMC-OA-Demo to view it.
Model Zoo
Check it out if you want to load model pretrained on PMC-OA directly.
We plan to release more models pretrained on PMC-OA. Feel free to reach us if the model you want is not included in model zoo for now. Also, we express our thanks to the help from the community.
| Model | Link | Provider |
|---|---|---|
| ViT-L-14 | https://huggingface.co/ryanyip7777/pmc_vit_l_14 | @ryanyip7777 |
Daraset Structure
PMC-OA (seperated images, separated caption).
images.zip: images folderpmc_oa.jsonl: dataset file of pmc-oapmc_oa_beta.jsonl: dataset file of pmc-oa-beta
-
train.jsonl: metafile of train set-
valid.jsonl: metafile of valid set- test.jsonl: metafile of test set
The difference between PMC-OA & PMC-OA-Beta lies in the methods of processing captions. In PMC-OA, we utilize ChatGPT to help us divide compound captions into seperate ones. While PMC-OA-Beta keeps all the compound ones without division.
Sample
A row in pmc_oa.jsonl is shown bellow,
{
"image": "PMC212319_Fig3_4.jpg",
"caption": "A. Real time image of the translocation of ARF1-GFP to the plasma membrane ...",
}
Explanation to each key
- image: path to the image
- caption: corresponding to the image
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