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https://github.com/huggingface/datasets/pull/7851 | 7,851 | Add fasta support | {
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https://github.com/huggingface/datasets/pull/7848 | 7,848 | DOC: remove mode parameter in docstring of pdf and video feature | {
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As mentioned in the issue `mode` has been copy-pasted but isn't used in these files. | {
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https://github.com/huggingface/datasets/pull/7847 | 7,847 | Better streaming retries (504 and 429) | {
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https://github.com/huggingface/datasets/pull/7846 | 7,846 | set dev version | {
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https://github.com/huggingface/datasets/pull/7845 | 7,845 | Release: 4.4.0 | {
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https://github.com/huggingface/datasets/pull/7844 | 7,844 | support fsspec 2025.10.0 | {
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https://github.com/huggingface/datasets/pull/7843 | 7,843 | fix column with transform | {
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https://github.com/huggingface/datasets/issues/7842 | 7,842 | Transform with columns parameter triggers on non-specified column access | {
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Iterating over a [`Column`](https://github.com/huggingface/datasets/blob/8b1bd4ec1cc9e9ce022f749abb6485ef984ae7c0/src/datasets/arrow_dataset.py#L633-L692) iterates through the parent [`Dataset`](https://github.com/huggingface/datasets/blob/8b1bd4ec1cc9e9ce022f749abb6485ef984ae7c0/src/datasets/arro... | {
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https://github.com/huggingface/datasets/issues/7841 | 7,841 | DOC: `mode` parameter on pdf and video features unused | {
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"They seem to be artefacts from a copy-paste of the Image feature ^^' we should remove them"
] | 2025-11-02T12:37:47Z | 2025-11-05T14:04:04Z | 2025-11-05T14:04:04Z | CONTRIBUTOR | null | null | Following up on https://github.com/huggingface/datasets/pull/7840 I asked claude code to check for undocumented parameters for other features and it found:
- mode parameter on video is documented but unused: https://github.com/huggingface/datasets/blob/main/src/datasets/features/video.py#L48-L49
- the same goes for the... | {
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https://github.com/huggingface/datasets/pull/7840 | 7,840 | Add num channels to audio | {
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"url": "https://api.github.com/repos/huggingface/datasets/pulls/... | Fixes #7837
We currently have the [mono attribute for Audio documented](https://github.com/huggingface/datasets/blob/41c05299348a499807432ab476e1cdc4143c8772/src/datasets/features/audio.py#L52C1-L54C22) but not used anywhere resulting in confusion for users. Since torchcodec does not know this attribute I suggest us... | {
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https://github.com/huggingface/datasets/issues/7839 | 7,839 | datasets doesn't work with python 3.14 | {
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"Thanks for the report.\nHave you tried on main? This should work, there was recently a PR merged to address this problem, see #7817",
"Works on main 👍 \nWhat's the release schedule for `datasets`? Seems like a cadence of ~2weeks so I assume a real version is due pretty soon?",
"let's say we do a new release l... | 2025-11-02T09:09:06Z | 2025-11-04T14:02:25Z | 2025-11-04T14:02:25Z | NONE | null | null | ### Describe the bug
Seems that `dataset` doesn't work with python==3.14. The root cause seems to be something with a `deel` API that was changed.
```
TypeError: Pickler._batch_setitems() takes 2 positional arguments but 3 were given
```
### Steps to reproduce the bug
(on a new folder)
uv init
uv python pin 3.14
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https://github.com/huggingface/datasets/issues/7837 | 7,837 | mono parameter to the Audio feature is missing | {
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"Hey, we removed the misleading passage in the docstring and enabled support for `num_channels` as torchcodec does",
"thanks!"
] | 2025-10-31T15:41:39Z | 2025-11-03T15:59:18Z | 2025-11-03T14:24:12Z | NONE | null | null | According to the docs, there is a "mono" parameter to the Audio feature, which turns any stereo into mono. In practice the signal is not touched and the mono parameter, even though documented, does not exist.
https://github.com/huggingface/datasets/blob/41c05299348a499807432ab476e1cdc4143c8772/src/datasets/features/a... | {
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https://github.com/huggingface/datasets/pull/7836 | 7,836 | Python 3.14 | {
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"The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_7836). All of your documentation changes will be reflected on that endpoint. The docs are available until 30 days after the last update."
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https://github.com/huggingface/datasets/pull/7835 | 7,835 | Add DICOM support | {
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"Awesome ! For the docs should we rename https://huggingface.co/docs/datasets/nifti_dataset to medical_imaging_dataset and have both DICOM and NIfTI together or have separate pages in you opinion ?",
"The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_7835). All of your document... | 2025-10-28T10:41:05Z | 2025-11-05T17:47:44Z | null | CONTRIBUTOR | false | {
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Add support for the dicom file format.
This PR follows PR #7815 and PR #7325 closely.
Remarkable differences:
I made sure that we can load all of pydicom's test data, and encountered the `force=True` parameter that we explicitly support here. This allows to trying to load corrupted dicom files, we... | null | {
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https://github.com/huggingface/datasets/issues/7834 | 7,834 | Audio.cast_column() or Audio.decode_example() causes Colab kernel crash (std::bad_alloc) | {
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"Hi ! `datasets` v4 uses `torchcodec` for audio decoding (previous versions were using `soundfile`). What is your `torchcodec` version ? Can you try other versions of `torchcodec` and see if it works ?",
"When I install `datasets` with `pip install datasets[audio]` it install this version of `torchcodec`:\n```\nN... | 2025-10-27T22:02:00Z | 2025-10-30T22:32:54Z | null | NONE | null | null | ### Describe the bug
When using the huggingface datasets.Audio feature to decode a local or remote (public HF dataset) audio file inside Google Colab, the notebook kernel crashes with std::bad_alloc (C++ memory allocation failure).
The crash happens even with a minimal code example and valid .wav file that can be read... | null | {
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https://github.com/huggingface/datasets/pull/7833 | 7,833 | Fix: Properly render [!TIP] block in stream.shuffle documentation | {
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"url": "https://api.github.com/repos/huggingface/datasets/pulls/... | The second line starting with the bracket doesn't properly render on huggingface/docs. Added "> " to address it.
In the client documentation, the markdown 'TIP' paragraph in docs/stream#shuffle is not well executed, not as the other in the same page / while markdown is correctly considering it.
Documentation:
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https://github.com/huggingface/datasets/issues/7832 | 7,832 | [DOCS][minor] TIPS paragraph not compiled in docs/stream | {
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Documentation:
https://huggingface.co/docs/datasets/v4.3.0/en/stream#shuffle:~:text=%5B!TIP%5D%5BIterableDataset.shuffle(... | {
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https://github.com/huggingface/datasets/pull/7831 | 7,831 | resolves the ValueError: Unable to avoid copy while creating an array | {
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"## Also i have done some tests on real dataset\r\n\r\n### Tested with real datasets:\r\n- ✅ IMDB dataset with NumPy 1.26.4 and 2.3.4\r\n- ✅ Rotten Tomatoes dataset with NumPy 1.26.4 and 2.3.4\r\n- ✅ Artificial datasets with ClassLabel features\r\n\r\n### Results:\r\n- Stratified splits work correctly in both NumPy... | 2025-10-25T08:13:54Z | 2025-10-29T06:35:32Z | 2025-10-28T16:10:43Z | CONTRIBUTOR | false | {
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"url": "https://api.github.com/repos/huggingface/datasets/pulls/... | ## Summary
Fixes #7818
This PR resolves the `ValueError: Unable to avoid copy while creating an array` error that occurs when using `train_test_split` with `stratify_by_column` parameter in NumPy 2.0+.
## Changes
- Wrapped the stratify column array access with `np.asarray()` in `arrow_dataset.py`
- This allow... | {
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https://github.com/huggingface/datasets/pull/7830 | 7,830 | fix ci compressionfs | {
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https://github.com/huggingface/datasets/issues/7829 | 7,829 | Memory leak / Large memory usage with num_workers = 0 and numerous dataset within DatasetDict | {
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"Thanks for the report, this is possibly related #7722 and #7694.\n\nCould you pls provide steps to reproduce this?",
"To overcome this issue right now I did simply reduce the size of the dataset and ended up running a for loop (my training has now a constant learning rate schedule). From what I understood, and I... | 2025-10-24T09:51:38Z | 2025-10-27T19:37:21Z | null | NONE | null | null | ### Describe the bug
Hi team, first off, I love the datasets library! 🥰
I'm encountering a potential memory leak / increasing memory usage when training a model on a very large DatasetDict.
Setup: I have a DatasetDict containing 362 distinct datasets, which sum up to ~2.8 billion rows.
Training Task: I'm performin... | null | {
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https://github.com/huggingface/datasets/pull/7828 | 7,828 | set dev version | {
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https://github.com/huggingface/datasets/pull/7827 | 7,827 | release: 4.3.0 | {
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https://github.com/huggingface/datasets/pull/7826 | 7,826 | picklable batch_fn | {
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https://github.com/huggingface/datasets/pull/7825 | 7,825 | Fix ArrowInvalid for large variables | {
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"@lhoestq : from what I see in the CI logs ( tests/test_arrow_dataset.py::test_map_int32_overflow \r\n/opt/hostedtoolcache/Python/3.9.23/x64/lib/python3.9/site-packages/multiprocess/resource_tracker.py:219: UserWarning: resource_tracker: There appear to be 24 leaked shared_memory objects to clean up at shutdown\r\n... | 2025-10-22T14:42:47Z | 2025-11-05T11:02:14Z | null | CONTRIBUTOR | false | {
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In addition to the solution proposed in the issue, I encountered we also need to support 64bit types when writing using the `RecordBatchStreamWriter`.
Not sure if we want to create such large objects in the CI, but this is the only way to test that the issue is fixed, therefore I added the unit test. | null | {
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https://github.com/huggingface/datasets/pull/7824 | 7,824 | Fix batch_size default description in to_polars docstrings | {
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https://github.com/huggingface/datasets/pull/7823 | 7,823 | Fix random seed on shuffle and interleave_datasets | {
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"Cool ! To avoid unwanted side effects it could be implemented for every class instead o... | 2025-10-17T10:21:47Z | 2025-10-24T14:21:22Z | 2025-10-24T14:04:36Z | CONTRIBUTOR | false | {
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"url": "https://api.github.com/repos/huggingface/datasets/pulls/... | closes #7567
Add `shift_rngs` method to `ExamplesIterable` that is called directly after sharding. If a generator is available (not the case for all subclasses) we update the seed of the generator by shifting by the worker_id.
~This is just the fix for `shuffle`, in the corresponding issue `interleave_datasets` i... | {
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https://github.com/huggingface/datasets/pull/7822 | 7,822 | Retry open hf file | {
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"url": "https://api.github.com/repos/huggingface/datasets/pulls/... | Fix this error
```python
File "/workdir/.venv/lib/python3.13/site-packages/datasets/utils/file_utils.py", line 934, in xopen
file_obj = fsspec.open(file, mode=mode, *args, **kwargs).open()
File "/workdir/.venv/lib/python3.13/site-packages/fsspec/core.py", line 147, in open
return self.__enter__()
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https://github.com/huggingface/datasets/issues/7821 | 7,821 | Building a dataset with large variable size arrays results in error ArrowInvalid: Value X too large to fit in C integer type | {
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"Thanks for reporting ! You can fix this by specifying the output type explicitly and use `LargeList` which uses int64 for offsets:\n\n```python\nfeatures = Features({\"audio\": LargeList(Value(\"uint16\"))})\nds = ds.map(..., features=features)\n```\n\nIt would be cool to improve `list_of_pa_arrays_to_pyarrow_list... | 2025-10-16T08:45:17Z | 2025-10-20T13:42:05Z | null | CONTRIBUTOR | null | null | ### Describe the bug
I used map to store raw audio waveforms of variable lengths in a column of a dataset the `map` call fails with ArrowInvalid: Value X too large to fit in C integer type.
```
Traceback (most recent call last):
Traceback (most recent call last):
File "...lib/python3.12/site-packages/multiprocess/p... | null | {
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https://github.com/huggingface/datasets/pull/7820 | 7,820 | Keep hffs cache in workers when streaming | {
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"url": "https://api.github.com/repos/huggingface/datasets/pulls/... | (and also reorder the hffs args to improve caching)
When using `DataLoader(iterable_dataset, num_workers=...)` the dataset is pickled and passed to the worker. However previously the resulting dataset would be in a process with an empty hffs cache. By keeping the cache attached to `IterableDataset`, the cached hffs ... | {
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https://github.com/huggingface/datasets/issues/7819 | 7,819 | Cannot download opus dataset | {
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"Hi ! it seems \"en-zh\" doesn't exist for this dataset\n\nYou can see the list of subsets here: https://huggingface.co/datasets/Helsinki-NLP/opus_books"
] | 2025-10-15T09:06:19Z | 2025-10-20T13:45:16Z | null | NONE | null | null | When I tried to download opus_books using:
from datasets import load_dataset
dataset = load_dataset("Helsinki-NLP/opus_books")
I got the following errors:
FileNotFoundError: Couldn't find any data file at /workspace/Helsinki-NLP/opus_books. Couldn't find 'Helsinki-NLP/opus_books' on the Hugging Face Hub either: Local... | null | {
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https://github.com/huggingface/datasets/issues/7818 | 7,818 | train_test_split and stratify breaks with Numpy 2.0 | {
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"I can't reproduce this. Could you pls provide an example with a public dataset/artificial dataset and show how you loaded that?\n\nThis works for me:\n\n```python\nimport numpy as np\nfrom datasets import Dataset, Features, ClassLabel, Value\n\ndata = {\"text\": [f\"sample_{i}\" for i in range(100)], \"label\": [i... | 2025-10-15T00:01:19Z | 2025-10-28T16:10:44Z | 2025-10-28T16:10:44Z | NONE | null | null | ### Describe the bug
As stated in the title, since Numpy changed in version >2.0 with copy, the stratify parameters break.
e.g. `all_dataset.train_test_split(test_size=0.2,stratify_by_column="label")` returns a Numpy error.
It works if you downgrade Numpy to a version lower than 2.0.
### Steps to reproduce the bug
... | {
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https://github.com/huggingface/datasets/pull/7817 | 7,817 | fix: better args passthrough for `_batch_setitems()` | {
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"@sghng There is a regression with python 3.13.8 when lm-eval is calling datasets load\r\n\r\n```python\r\nself = <test_llama3_2.TestLlama3_2 testMethod=test_llama3_2>\r\n\r\n def test_llama3_2(self):\r\n> self.quant_lm_eval()\r\n\r\ntests/models/test_llama3_2.py:35: \r\n_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ ... | 2025-10-14T22:51:51Z | 2025-10-28T17:32:12Z | 2025-10-27T17:08:25Z | CONTRIBUTOR | false | {
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"url": "https://api.github.com/repos/huggingface/datasets/pulls/... | In Python 3.14, there's a change in the signature of `_Pickler._batch_setitems`.
It's changed to:
```python
# pickle.py
def _batch_setitems(self, items, obj):
# Helper to batch up SETITEMS sequences; proto >= 1 only
save = self.save
write = self.write
```
To accomodate this, in `dill`, we h... | {
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https://github.com/huggingface/datasets/issues/7816 | 7,816 | disable_progress_bar() not working as expected | {
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"@xianbaoqian ",
"Closing this one since it's a Xet issue."
] | 2025-10-14T03:25:39Z | 2025-10-14T23:49:26Z | 2025-10-14T23:49:26Z | NONE | null | null | ### Describe the bug
Hi,
I'm trying to load a dataset on Kaggle TPU image. There is some known compat issue with progress bar on Kaggle, so I'm trying to disable the progress bar globally. This does not work as you can see in [here](https://www.kaggle.com/code/windmaple/hf-datasets-issue).
In contract, disabling pro... | {
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https://github.com/huggingface/datasets/pull/7815 | 7,815 | Add nifti support | {
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"The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_7815). All of your documentation changes will be reflected on that endpoint. The docs are available until 30 days after the last update.",
"Btw I couldn't resist but share your PR with the community online on twitter already, I... | 2025-10-13T20:07:32Z | 2025-11-06T09:44:34Z | 2025-10-24T13:22:18Z | CONTRIBUTOR | false | {
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supports #7804
This PR follows https://github.com/huggingface/datasets/pull/7325 very closely
I am a bit unsure what we need to add to the `document_dataset.mdx` and `document_load.mdx`. I should probably create a dataset on the hub first to create this guide instead of copy+pasting from... | {
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https://github.com/huggingface/datasets/pull/7814 | 7,814 | Allow streaming hdf5 files | {
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## Details
in `datasets` loaders, `open()` is extended to work with files that are on disk but also on HF. Files on HF are streamed using HTTP range requests using the `HfFileSystem` implementation in the `huggingface_hu... | {
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https://github.com/huggingface/datasets/issues/7813 | 7,813 | Caching does not work when using python3.14 | {
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"https://github.com/uqfoundation/dill/issues/725",
"@intexcor does #7817 fix your problem?"
] | 2025-10-10T15:36:46Z | 2025-10-27T17:08:26Z | 2025-10-27T17:08:26Z | NONE | null | null | ### Describe the bug
Traceback (most recent call last):
File "/workspace/ctn.py", line 8, in <module>
ds = load_dataset(f"naver-clova-ix/synthdog-{lang}") # или "synthdog-zh" для китайского
File "/workspace/.venv/lib/python3.14/site-packages/datasets/load.py", line 1397, in load_dataset
builder_instance =... | {
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https://github.com/huggingface/datasets/pull/7812 | 7,812 | docs: document_dataset PDFs & OCR | {
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https://github.com/huggingface/datasets/issues/7811 | 7,811 | SIGSEGV when Python exits due to near null deref | {
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"The issue seems to come from `dill` which is a `datasets` dependency, e.g. this segfaults:\n\n```python\nimport dill\nfrom tqdm import tqdm\nprogress_bar = tqdm(total=(1000), unit='cols', desc='cols ')\nprogress_bar.update(1)\n```\n\n`tqdm` seems to segfault when `dill` is imported. I only found this about segfaul... | 2025-10-09T22:00:11Z | 2025-10-10T22:09:24Z | null | NONE | null | null | ### Describe the bug
When I run the following python script using datasets I get a segfault.
```python
from datasets import load_dataset
from tqdm import tqdm
progress_bar = tqdm(total=(1000), unit='cols', desc='cols ')
progress_bar.update(1)
```
```
% lldb -- python3 crashmin.py
(lldb) target create "python3"
Cur... | null | {
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https://github.com/huggingface/datasets/pull/7810 | 7,810 | fix conda deps | {
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https://github.com/huggingface/datasets/pull/7809 | 7,809 | Set dev version | {
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https://github.com/huggingface/datasets/pull/7808 | 7,808 | release: 4.2.0 | {
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https://github.com/huggingface/datasets/pull/7807 | 7,807 | typo | {
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https://github.com/huggingface/datasets/pull/7806 | 7,806 | Parquet: add `on_bad_file` argument to error/warn/skip bad files | {
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"url": "https://api.github.com/repos/huggingface/datasets/pulls/... | ```python
from datasets import load_dataset
on_bad_file = "error" # default
# on_bad_file = "warn" # warn and skip bad file
# on_bad_file = "skip" # skip bad file
ds = load_dataset(parquet_dataset_id, on_bad_file=on_bad_file)
``` | {
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https://github.com/huggingface/datasets/pull/7805 | 7,805 | Less api calls when resolving data_files | {
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I disabled multithreading, which was actually not useful anymore since `HfFileSystem` has been using caching for a while now. | {
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https://github.com/huggingface/datasets/issues/7804 | 7,804 | Support scientific data formats | {
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"Please add the support for `Zarr`! That's what we use in the Bioimaging community. It is crucial, because raw upload of a *single* bio image can take _terrabytes in memory_!\n\nThe python library would be `bioio` or `zarr`:\n- [ ] Zarr: `bioio` or `zarr`\n\nSee a [Zarr example](https://ome.github.io/ome-ngff-valid... | 2025-10-09T10:18:24Z | 2025-10-31T14:41:29Z | null | MEMBER | null | null | List of formats and libraries we can use to load the data in `datasets`:
- [ ] DICOMs: pydicom
- [x] NIfTIs: nibabel
- [ ] WFDB: wfdb
cc @zaRizk7 for viz
Feel free to comment / suggest other formats and libs you'd like to see or to share your interest in one of the mentioned format | null | {
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https://github.com/huggingface/datasets/pull/7803 | 7,803 | More Parquet streaming docs | {
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https://github.com/huggingface/datasets/issues/7802 | 7,802 | [Docs] Missing documentation for `Dataset.from_dict` | {
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"Hi I'd like to work on this. I can see the docstring is already in the code. \nCould you confirm:\n1. Is this still available?\n2. Should I add this to the main_classes.md file, or is there a specific \n documentation file I should update?\n3. Are there any form... | 2025-10-09T02:54:41Z | 2025-10-19T16:09:33Z | null | NONE | null | null | Documentation link: https://huggingface.co/docs/datasets/en/package_reference/main_classes
Link to method (docstring present): https://github.com/huggingface/datasets/blob/6f2502c5a026caa89839713f6f7c8b958e5e83eb/src/datasets/arrow_dataset.py#L1029
The docstring is present for the function, but seems missing from the... | null | {
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https://github.com/huggingface/datasets/pull/7801 | 7,801 | Add parquet scan options and docs | {
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"The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_7801). All of your documentation changes will be reflected on that endpoint. The docs are available until 30 days after the last update."
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https://github.com/huggingface/datasets/pull/7800 | 7,800 | Fix polars cast column image | {
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"The Image() type is set to have a storage of `string` for \"path\" and not `large_string`. Therefore while your change does work to do the conversion, it can create issues in other places. For example I'm pretty sure you wouldn't be able to concatenate the resulting dataset with a dataset with Image() using `strin... | 2025-10-08T10:01:18Z | 2025-10-18T13:48:37Z | 2025-10-13T14:39:47Z | CONTRIBUTOR | false | {
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"url": "https://api.github.com/repos/huggingface/datasets/pulls/... | Fixes #7765
The problem here is that polars uses pyarrow large_string for images, while pandas and others just use the string type. This PR solves that and adds a test.
```python
import polars as pl
from datasets import Dataset
import pandas as pd
import pyarrow as pa
from pathlib import Path
shared_data... | {
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https://github.com/huggingface/datasets/pull/7799 | 7,799 | Define CI future | {
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"The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_7799). All of your documentation changes will be reflected on that endpoint. The docs are available until 30 days after the last update."
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https://github.com/huggingface/datasets/issues/7798 | 7,798 | Audio dataset is not decoding on 4.1.1 | {
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"Previously (datasets<=3.6.0), audio columns were decoded automatically when accessing a row. Now, for performance reasons, audio decoding is lazy by default: you just see the file path unless you explicitly cast the column to Audio.\n\nHere’s the fix (following the current [datasets audio docs](https://huggingface... | 2025-10-05T06:37:50Z | 2025-10-06T14:07:55Z | null | NONE | null | null | ### Describe the bug
The audio column remain as non-decoded objects even when accessing them.
```python
dataset = load_dataset("MrDragonFox/Elise", split = "train")
dataset[0] # see that it doesn't show 'array' etc...
```
Works fine with `datasets==3.6.0`
Followed the docs in
- https://huggingface.co/docs/dataset... | null | {
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https://github.com/huggingface/datasets/pull/7797 | 7,797 | Datasets: Add WMT21 & WMT22 loaders (basic TSV loaders, sample data, tests) | {
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"closing since datasets should be added on https://huggingface.co directly"
] | 2025-10-01T10:46:01Z | 2025-10-10T15:33:25Z | 2025-10-10T15:33:25Z | NONE | false | {
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} | - Implemented TSV-based dataset loaders:
- WMT21Dataset (local_datasets/wmt21/wmt21_dataset.py)
- WMT22Dataset (local_datasets/wmt22/wmt22_dataset.py)
These classes load source-target pairs from .tsv files for train, validation, and test splits.
- Created sample dummy data for both datasets:
- dummy_da... | {
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https://github.com/huggingface/datasets/pull/7796 | 7,796 | Docs: fix typo, improve readability, add code comments | {
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} | What I did:
- Fixed a small typo in README to improve clarity
- Fixed repeated word "frameworks frameworks"
- Split long paragraphs into shorter sentences for readability
- Added # Example comments before code blocks for clarity
Why:
- Helps new users avoid confusion
How I tested:
- Checked locally in Markd... | null | {
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https://github.com/huggingface/datasets/pull/7795 | 7,795 | Add pyarrow's binary view to features | {
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https://github.com/huggingface/datasets/pull/7794 | 7,794 | Fix nested data conversions error in parquet loading (fixes #7793) | {
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"Unfortunately, I'm running into this error:\r\n```\r\n~/scratch » uv run python test_hf.py \r\nResolving data file... | 2025-09-27T22:04:13Z | 2025-10-01T16:56:20Z | null | NONE | false | {
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} | Fixes #7793
## Problem
Loading datasets with deeply nested structures (like `metr-evals/malt-public`) fails with:
ArrowNotImplementedError: Nested data conversions not implemented for chunked array outputs
This occurs when parquet files contain nested data (lists, structs, maps) that exceed PyArrow's 16MB chun... | null | {
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https://github.com/huggingface/datasets/issues/7793 | 7,793 | Cannot load dataset, fails with nested data conversions not implemented for chunked array outputs | {
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"Hey @neevparikh,\nThanks for reporting this! I can reproduce the issue and have identified the root cause.\nProblem: The metr-evals/malt-public dataset contains deeply nested conversation data that exceeds PyArrow's 16MB chunk limit. When PyArrow tries to read it in chunks, it hits a fundamental limitation: \"Nest... | 2025-09-27T01:03:12Z | 2025-09-27T21:35:31Z | null | NONE | null | null | ### Describe the bug
Hi! When I load this dataset, it fails with a pyarrow error. I'm using datasets 4.1.1, though I also see this with datasets 4.1.2
To reproduce:
```
import datasets
ds = datasets.load_dataset(path="metr-evals/malt-public", name="irrelevant_detail")
```
Error:
```
Traceback (most recent call las... | null | {
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https://github.com/huggingface/datasets/issues/7792 | 7,792 | Concatenate IterableDataset instances and distribute underlying shards in a RoundRobin manner | {
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"# With `datasets.Dataset`\n\nHere is an small script that shows the distribution differences of samples between `interleave_datasets`, `concatenate_datasets` and `concatenate_datasets` + shuffling.\n\n```python\nimport datasets as hf_datasets\n\ndef gen(dataset: int, n_samples: int):\n for i in range(n_samples)... | 2025-09-26T10:05:19Z | 2025-10-15T18:05:23Z | 2025-10-15T18:05:23Z | NONE | null | null | ### Feature request
I would like to be able to concatenate multiple `IterableDataset` with possibly different features. I would like to then be able to stream the results in parallel (both using DDP and multiple workers in the pytorch DataLoader). I want the merge of datasets to be well balanced between the different ... | {
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https://github.com/huggingface/datasets/pull/7791 | 7,791 | fix: add `num_proc` argument to `Dataset.to_sql` | {
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"Hi ! could you also write a test to make sure this works fine ?\r\n\r\n(in case there needs to be a special logic to handle the concurrent writes to the database)",
"Hi @lhoestq \r\nDone! Let me know if more is needed :)"
] | 2025-09-25T15:02:46Z | 2025-10-18T13:21:16Z | null | NONE | false | {
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} | **Task Done:**
- Resolve issue #7788 : Add the missing argument mapping in Dataset.to_sql (`src/datasets/arrow_dataset.py`)
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https://github.com/huggingface/datasets/pull/7790 | 7,790 | update tips in docs | {
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"The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_7790). All of your documentation changes will be reflected on that endpoint. The docs are available until 30 days after the last update.",
"cc @mishig25"
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https://github.com/huggingface/datasets/pull/7789 | 7,789 | fix link for rotten_tomatoes dataset | {
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https://github.com/huggingface/datasets/issues/7788 | 7,788 | `Dataset.to_sql` doesn't utilize `num_proc` | {
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https://github.com/huggingface/datasets/pull/7787 | 7,787 | feat: avoid some copies in torch formatter | {
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"can you re-read your PR please ?"
] | 2025-09-24T20:19:44Z | 2025-09-26T15:04:25Z | 2025-09-26T15:04:23Z | CONTRIBUTOR | false | {
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"url": "https://api.github.com/repos/huggingface/datasets/pulls/... | ## perf: reduce copies in TorchFormatter
This PR make changes the torch formatter to avoid unnecessary copies and casts when converting decoded batches to tensors.
Because many arrays are already in a torch-friendly memory layout and dtype, we can do zero‑copy conversions (`torch.from_numpy`) and only fall back t... | {
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https://github.com/huggingface/datasets/pull/7786 | 7,786 | Sample without replacement option when interleaving datasets | {
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"@lhoestq Continuing on the idea from https://github.com/huggingface/datasets/issues/217 \r\nThis doesn't add a new stopping criteria, but a new argument to interleave_datasets method. Let me know what you think and if you see a better way of doing this I'm open to suggestions.",
"Great ! this is a cool additions... | 2025-09-24T09:18:14Z | 2025-10-07T14:50:16Z | 2025-10-07T14:50:16Z | CONTRIBUTOR | false | {
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"url": "https://api.github.com/repos/huggingface/datasets/pulls/... | Right now, `interleave_datasets` function with probabilities will sample with replacement. The PR adds the ability to sample without replacement.
```
import datasets
# Create datasets of different sizes to test exhaustion
data_a = [{"value": i, "source": "A"} for i in range(5)]
data_b = [{"value": i, "source":... | {
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https://github.com/huggingface/datasets/pull/7785 | 7,785 | Fix Audio docstring by removing unsupported mono argument | {
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"I think we can keep the arg and add the missing torch.mean() in the Audio.decode_example method",
"> I think we can keep the arg and add the missing torch.mean() in the Audio.decode_example method\r\n\r\nThank you @lhoestq. I will add torch.mean().",
"fixed by #7840 "
] | 2025-09-22T09:06:52Z | 2025-11-03T14:52:28Z | 2025-11-03T14:52:27Z | CONTRIBUTOR | false | {
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} | This PR fixes issue #7745.
Who can review:
@lhoestq | {
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https://github.com/huggingface/datasets/pull/7783 | 7,783 | Support huggingface_hub v0.x and v1.x | {
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"The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_7783). All of your documentation changes will be reflected on that endpoint. The docs are available until 30 days after the last update.",
"@lhoestq could you have a look at this PR please? It makes `datasets` compatible with t... | 2025-09-18T14:45:20Z | 2025-10-01T13:56:05Z | 2025-10-01T13:56:03Z | CONTRIBUTOR | false | {
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"url": "https://api.github.com/repos/huggingface/datasets/pulls/... | Related to https://github.com/huggingface/huggingface_hub/issues/3340.
This PR adapts `datasets` to be compatible with both huggingface_hub v0.x and v1.x.
In practice nothing else should change (I've checked the codebase). The `HfHubHTTPError` is a base error defined in `huggingface_hub` that inherits from `requ... | {
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https://github.com/huggingface/datasets/pull/7782 | 7,782 | set dev version | {
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https://github.com/huggingface/datasets/pull/7781 | 7,781 | release: 4.1.1 | {
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https://github.com/huggingface/datasets/issues/7780 | 7,780 | BIGPATENT dataset inaccessible (deprecated script loader) | {
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"Hi ! I opened https://huggingface.co/datasets/NortheasternUniversity/big_patent/discussions/7 to update the dataset, hopefully it's merged soon !",
"The dataset now works with `datasets` v4 ! closing this issue"
] | 2025-09-18T08:25:34Z | 2025-09-25T14:36:13Z | 2025-09-25T14:36:13Z | NONE | null | null | dataset: https://huggingface.co/datasets/NortheasternUniversity/big_patent
When I try to load it with the datasets library, it fails with:
RuntimeError: Dataset scripts are no longer supported, but found big_patent.py
Could you please publish a Parquet/Arrow export of BIGPATENT on the Hugging Face so that it can be... | {
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https://github.com/huggingface/datasets/pull/7779 | 7,779 | fix empty dataset to_parquet | {
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https://github.com/huggingface/datasets/pull/7778 | 7,778 | [FIX] force spawning pool for MacOS | {
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"After more discussions on slack, we can switch the default to spawn.\r\n\r\nLet's use m... | 2025-09-17T11:38:38Z | 2025-09-18T17:04:45Z | null | NONE | true | {
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} | This PR gets multiprocessing to work on mac os:
```python
from datasets import load_dataset
ds = load_dataset("fka/awesome-chatgpt-prompts", split="train").take(100)
ds = ds.map(lambda x: x, num_proc=4)
ds.push_to_hub("burtenshaw/dataset-test", num_proc=4)
``` | null | {
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https://github.com/huggingface/datasets/issues/7777 | 7,777 | push_to_hub not overwriting but stuck in a loop when there are existing commits | {
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"HTTP 412 means a commit happened in the meantime, so `get_deletions_and_dataset_card` has to retry to get the latest version of the dataset card and what files to delete based on the latest version of the dataset repository\n\nAre you running other operations in the dataset repo for your push_to_hub ?",
"There w... | 2025-09-17T03:15:35Z | 2025-09-17T19:31:14Z | 2025-09-17T19:31:14Z | NONE | null | null | ### Describe the bug
`get_deletions_and_dataset_card` stuck at error a commit has happened error since push to hub for http error 412 for tag 4.1.0. The error does not exists in 4.0.0.
### Steps to reproduce the bug
Create code to use push_to_hub, ran twice each time with different content for datasets.Dataset.
The... | {
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https://github.com/huggingface/datasets/pull/7776 | 7,776 | [docs] Fix broken WebDataset link on “Create a video dataset” page | {
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} | ### What
Fix the "WebDataset documentation" link on the Create a video dataset page to point
to the correct section on the video load guide.
### Why
The link currently points to an external repo, but the Hugging Face docs
have an internal "WebDataset" section under video_load.
### How
- docs/source/video_dat... | {
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https://github.com/huggingface/datasets/pull/7775 | 7,775 | fix iterate nested field | {
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https://github.com/huggingface/datasets/pull/7774 | 7,774 | Set dev version | {
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https://github.com/huggingface/datasets/pull/7773 | 7,773 | Release: 4.1.0 | {
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https://github.com/huggingface/datasets/issues/7772 | 7,772 | Error processing scalar columns using tensorflow. | {
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"Using tf.convert_to_tensor works fine:\n\n```\nimport tensorflow as tf\n\nstart_pos = tf.convert_to_tensor(train_ds['start_positions'], dtype=tf.int64)\nstart_pos = tf.reshape(start_pos, [-1, 1])\n```\n\n\nAlternatively, using the built-in to_tf_dataset also avoids the issue:\n\n```\ntrain_tf = train_ds.to_tf_data... | 2025-09-15T10:36:31Z | 2025-09-27T08:22:44Z | null | NONE | null | null | `datasets==4.0.0`
```
columns_to_return = ['input_ids','attention_mask', 'start_positions', 'end_positions']
train_ds.set_format(type='tf', columns=columns_to_return)
```
`train_ds`:
```
train_ds type: <class 'datasets.arrow_dataset.Dataset'>, shape: (1000, 9)
columns: ['question', 'sentences', 'answer', 'str_idx', 'en... | null | {
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https://github.com/huggingface/datasets/pull/7771 | 7,771 | Add support for arrow iterable when concatenating or interleaving | {
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"Seeing the following numbers on the script shared in the original issue. (MacBook Pro M4)\r\n\r\n```\r\n1000it [00:00, 4074.63it/s] # ds_a.with_format(\"torch\")\r\n1000it [00:01, 593.39it/s] # ds_a.shuffle()\r\n1999it [00:03, 594.09it/s] # datasets.interleave_datasets([ds_a, ds_b])\r\n1000it [00:00, 5382.45it/s] ... | 2025-09-14T06:40:50Z | 2025-09-17T16:51:28Z | 2025-09-17T16:51:28Z | CONTRIBUTOR | false | {
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"url": "https://api.github.com/repos/huggingface/datasets/pulls/... | Fixes a case when concatenating or interleaving datasets with `with_format(...)` call was slower.
Details here: https://github.com/huggingface/datasets/issues/6637
@lhoestq I tried to minimize the duplication between iter and iter_arrow methods, not sure if this is against the design, can separate those if needed. | {
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https://github.com/huggingface/datasets/pull/7770 | 7,770 | Fix: Correct float feature generation in `generate_examples` | {
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"Hi @lhoestq, just a gentle follow-up on this PR."
] | 2025-09-13T17:37:09Z | 2025-09-28T12:43:04Z | null | CONTRIBUTOR | false | {
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**Key changes include:**
* Added explic... | null | {
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https://github.com/huggingface/datasets/pull/7769 | 7,769 | Fix: Correct float feature generation in `generate_examples` | {
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**Key changes include:**
1. Added explicit... | {
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https://github.com/huggingface/datasets/pull/7768 | 7,768 | Custom `dl_manager` in `load_dataset` | {
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https://github.com/huggingface/datasets/issues/7767 | 7,767 | Custom `dl_manager` in `load_dataset` | {
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https://github.com/huggingface/datasets/blob/4.0.0/src/datasets/load.py#L1411-L1418
```
def load_dataset(
...
dl_manager: Optional[DownloadManager] = None, # add this new argument
**config_kwargs,
) -> Union[DatasetDict, Dataset, IterableDatasetDict, IterableDataset]:
...
# ... | null | {
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https://github.com/huggingface/datasets/issues/7766 | 7,766 | cast columns to Image/Audio/Video with `storage_options` | {
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"A",
"1",
"1",
"Ok",
"> ### Feature request\n> Allow `storage_options` to be passed in\n> \n> 1. `cast` related operations (e.g., `cast_columns, cast`)\n> 2. `info` related reading (e.g., `from_dict, from_pandas, from_polars`) together with `info.features`\n> \n> import datasets\n> \n> image_path = \"s3://b... | 2025-09-12T18:51:01Z | 2025-09-27T08:14:47Z | null | NONE | null | null | ### Feature request
Allow `storage_options` to be passed in
1. `cast` related operations (e.g., `cast_columns, cast`)
2. `info` related reading (e.g., `from_dict, from_pandas, from_polars`) together with `info.features`
```python3
import datasets
image_path = "s3://bucket/sample.png"
dataset = datasets.Dataset.from_d... | null | {
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https://github.com/huggingface/datasets/issues/7765 | 7,765 | polars dataset cannot cast column to Image/Audio/Video | {
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"I fixed this with a combination of `to_dict` and `from_dict`:\n\n```py\ndatasets.Dataset.from_dict(df.to_dict(as_series=False))\n```",
"@samuelstevens Yeah, I'm using similar workaround as well. But it would be ideal if we can avoid the copy."
] | 2025-09-12T18:32:49Z | 2025-10-13T14:39:48Z | 2025-10-13T14:39:48Z | NONE | null | null | ### Describe the bug
`from_polars` dataset cannot cast column to Image/Audio/Video, while it works on `from_pandas` and `from_dict`
### Steps to reproduce the bug
```python3
import datasets
import pandas as pd
import polars as pl
image_path = "./sample.png"
# polars
df = pl.DataFrame({"image_path": [image_path]})
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https://github.com/huggingface/datasets/pull/7764 | 7,764 | update torchcodec in ci | {
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"The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_7764). All of your documentation changes will be reflected on that endpoint. The docs are available until 30 days after the last update."
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https://github.com/huggingface/datasets/pull/7763 | 7,763 | Bump dill to 0.4.0 | {
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"Have you tried to run `pytest tests/test_fingerprint.py` ? It seems dill 0.3.9 breaks a lot of tests\r\n\r\n```\r\nFAILED tests/test_fingerprint.py::TokenizersHashTest::test_hash_regex - NameError: name 'log' is not defined\r\nFAILED tests/test_fingerprint.py::TokenizersHashTest::test_hash_tokenizer - NameError: n... | 2025-09-11T19:43:16Z | 2025-09-15T08:37:48Z | 2025-09-15T08:37:48Z | CONTRIBUTOR | false | {
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"url": "https://api.github.com/repos/huggingface/datasets/pulls/... | This bumps `dill` to 0.3.9 and closes #7510
It turns out the only thing required to make the tests pass was to extend the version checks to include 0.3.9. | {
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https://github.com/huggingface/datasets/pull/7762 | 7,762 | Parquet: use data page v2 for efficient page pruning | {
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"The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_7762). All of your documentation changes will be reflected on that endpoint. The docs are available until 30 days after the last update.",
"Closing this since it looks like the page offset index is enough :)"
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} | This is needed to enable page pruning with DataFusion, which will be useful for the Dataset Viewer.
Indeed page pruning with DataFusion allows to download only certain pages of a row group, reducing the I/O required to read just a few rows.
But while data page v1 generally works, it's not easy with DataFusion to ... | {
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https://github.com/huggingface/datasets/pull/7761 | 7,761 | Audio: use TorchCodec instead of Soundfile for encoding | {
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"The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_7761). All of your documentation changes will be reflected on that endpoint. The docs are available until 30 days after the last update."
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https://github.com/huggingface/datasets/issues/7760 | 7,760 | Hugging Face Hub Dataset Upload CAS Error | {
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"cc @jsulz maybe ?",
"Curious! I took a look at this and was unable to see why this would be occurring on our side. Tagging in @jgodlew and @bpronan since they might have insights. \n\n@n-bkoe just a few questions if you wouldn't mind: \n1. What kind of data are you uploading and what is the difference in file si... | 2025-09-10T10:01:19Z | 2025-09-16T20:01:36Z | null | NONE | null | null | ### Describe the bug
Experiencing persistent 401 Unauthorized errors when attempting to upload datasets to Hugging Face Hub using the `datasets` library. The error occurs specifically with the CAS (Content Addressable Storage) service during the upload process. Tried using HF_HUB_DISABLE_XET=1. It seems to work for sm... | null | {
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https://github.com/huggingface/datasets/issues/7759 | 7,759 | Comment/feature request: Huggingface 502s from GHA | {
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"g... | [] | open | false | [] | 2025-09-09T11:59:20Z | 2025-09-09T13:02:28Z | null | NONE | null | null | This is no longer a pressing issue, but for completeness I am reporting that in August 26th, GET requests to `https://datasets-server.huggingface.co/info\?dataset\=livebench/math` were returning 502s when invoked from [github actions](https://github.com/UKGovernmentBEIS/inspect_evals/actions/runs/17241892475/job/489211... | null | {
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https://github.com/huggingface/datasets/issues/7758 | 7,758 | Option for Anonymous Dataset link | {
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] | open | false | [] | 2025-09-08T20:20:10Z | 2025-09-08T20:20:10Z | null | NONE | null | null | ### Feature request
Allow for anonymized viewing of datasets. For instance, something similar to [Anonymous GitHub](https://anonymous.4open.science/).
### Motivation
We generally publish our data through Hugging Face. This has worked out very well as it's both our repository and archive (thanks to the DOI feature!).... | null | {
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https://github.com/huggingface/datasets/issues/7757 | 7,757 | Add support for `.conll` file format in datasets | {
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"That would be cool ! feel free to ping me if I can help reviewing a PR"
] | 2025-09-06T07:25:39Z | 2025-09-10T14:22:48Z | null | NONE | null | null | ### Feature request
I’d like to request native support in the Hugging Face datasets library for reading .conll files (CoNLL format). This format is widely used in NLP tasks, especially for Named Entity Recognition (NER), POS tagging, and other token classification problems.
Right now `.conll` datasets need to be manu... | null | {
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https://github.com/huggingface/datasets/issues/7756 | 7,756 | datasets.map(f, num_proc=N) hangs with N>1 when run on import | {
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If you `import` a module that runs `datasets.map(f, num_proc=N)` at the top-level, Python hangs.
### Steps to reproduce the bug
1. Create a file that runs datasets.map at the top-level:
```bash
cat <<EOF > import_me.py
import datasets
the_dataset = datasets.load_dataset("openai/openai_humanev... | null | {
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https://github.com/huggingface/datasets/pull/7755 | 7,755 | Support pathlib.Path for feature input | {
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"The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_7755). All of your documentation changes will be reflected on that endpoint. The docs are available until 30 days after the last update."
] | 2025-09-05T02:38:07Z | 2025-09-10T15:19:35Z | 2025-09-10T15:19:35Z | CONTRIBUTOR | false | {
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https://github.com/huggingface/datasets/pull/7754 | 7,754 | Add columns support to JSON loader | {
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} | New fix to #7594
This PR adds support for the columns argument in the JSON dataset builder.
Added columns parameter to JsonConfig.
Applied column filtering after table creation, filling missing columns with None.
Extended tests to cover:
- Selecting a subset of columns
- Handling missing requested columns
- Co... | null | {
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https://github.com/huggingface/datasets/issues/7753 | 7,753 | datasets massively slows data reads, even in memory | {
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"Hi ! you should try\n\n```python\nfrom datasets import Array3D, Dataset, Features, Value\n\nfeatures = Features({\"image\": Array3D(shape=(3, 224, 224), dtype=\"uint8\"), \"label\": Value(\"uint8\")})\nhf_dataset = Dataset.from_dict({'image': images, 'label':labels}, features=features)\n```\n\notherwise the type o... | 2025-09-04T01:45:24Z | 2025-09-18T22:08:51Z | null | NONE | null | null | ### Describe the bug
Loading image data in a huggingface dataset results in very slow read speeds, approximately 1000 times longer than reading the same data from a pytorch dataset. This applies even when the dataset is loaded into RAM using a `keep_in_memory=True` flag.
The following script reproduces the result wit... | null | {
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https://github.com/huggingface/datasets/pull/7752 | 7,752 | Fix: Update Dill Version in Setup py | {
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"same as https://github.com/huggingface/datasets/pull/7763: some tests need to be fixed to support 0.4.0",
"fixed by #7763 "
] | 2025-08-27T07:39:51Z | 2025-11-03T14:52:58Z | 2025-11-03T14:52:58Z | NONE | false | {
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} | Currently the DIll version is less than 3.9 and now major libraries like Multiprocess, gepa requires Dill version as 0.4.0 and this is making a conflict in installation. So added this small PR to update the DIll. | {
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https://github.com/huggingface/datasets/issues/7751 | 7,751 | Dill version update | {
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] | 2025-08-27T07:38:30Z | 2025-09-10T14:24:02Z | null | NONE | null | null | ### Describe the bug
Why the datasets is not updating the dill ?
Just want to know if I update the dill version in dill what will be the repucssion.
For now in multiplaces I have to update the library like process requirequire dill 0.4.0 so why not datasets.
Adding a pr too.
### Steps to reproduce the bug
.
###... | null | {
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https://github.com/huggingface/datasets/pull/7750 | 7,750 | Refactor: use unpacking in load.py for time and memory improvement | {
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} | In `src/datasets/load.py`, we can use unpacking rather than concatenating two lists for improved time and memory performance. It’s a small improvement in absolute terms, but a consistent and measurable one:
```diff
- ALL_ALLOWED_EXTENSIONS = list(_EXTENSION_TO_MODULE.keys()) + [".zip"]
+ ALL_ALLOWED_EXTENSIONS = [... | null | {
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