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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"
] | 2025-11-02T12:37:47 | 2025-11-05T14:04:04 | 2025-11-05T14:04:04 | 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... | 2025-11-02T09:09:06 | 2025-11-04T14:02:25 | 2025-11-04T14:02:25 | 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!"
] | 2025-10-31T15:41:39 | 2025-11-03T15:59:18 | 2025-11-03T14:24:12 | 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... | 2025-10-28T10:41:05 | 2025-11-05T17:47:44 | 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... | 2025-10-27T22:02:00 | 2025-10-30T22:32:54 | 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:
ht... | {
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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... | 2025-10-25T08:13:54 | 2025-10-29T06:35:32 | 2025-10-28T16:10:43 | 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... | 2025-10-24T09:51:38 | 2025-10-27T19:37:21 | 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... | 2025-10-22T14:42:47 | 2025-11-05T11:02:14 | 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... | 2025-10-17T10:21:47 | 2025-10-24T14:21:22 | 2025-10-24T14:04:36 | 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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```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... | 2025-10-16T08:45:17 | 2025-10-20T13:42:05 | 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"
] | 2025-10-15T09:06:19 | 2025-10-20T13:45:16 | 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... | 2025-10-15T00:01:19 | 2025-10-28T16:10:44 | 2025-10-28T16:10:44 | 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_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ ... | 2025-10-14T22:51:51 | 2025-10-28T17:32:12 | 2025-10-27T17:08:25 | 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."
] | 2025-10-14T03:25:39 | 2025-10-14T23:49:26 | 2025-10-14T23:49:26 | 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... | 2025-10-13T20:07:32 | 2025-11-06T09:44:34 | 2025-10-24T13:22:18 | 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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"url": "https://api.github.com/repos/huggingface/datasets/pulls/... | Add streaming support after https://github.com/huggingface/datasets/pull/7690, cc @klamike :)
## 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?"
] | 2025-10-10T15:36:46 | 2025-10-27T17:08:26 | 2025-10-27T17:08:26 | 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... | 2025-10-09T22:00:11 | 2025-10-10T22:09:24 | 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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Dataset Card for Dataset Name
This dataset is an upload linked with the HuggingFace LLM course, chapter 5. The goal was to create an own dataset and upload it to the Dataset Hub.
Dataset Details
Dataset Description
This dataset contains issues from the HuggingFace Dataset GitHub page (as of 05-11-2025). Pull issues as well as irrelevant API data were filtered out. The content of the comments on any issue were added.
Uses
The dataset can be used for simple text classification or text retrieval tasks. Summarization tasks are also possible.
Dataset Structure
Structure of Dataset: Dataset({ features: ['url', 'repository_url', 'labels_url', 'comments_url', 'events_url', 'html_url', 'id', 'node_id', 'number', 'title', 'user', 'labels', 'state', 'locked', 'assignee', 'assignees', 'milestone', 'comments', 'created_at', 'updated_at', 'closed_at', 'author_association', 'active_lock_reason', 'pull_request', 'body', 'timeline_url', 'performed_via_github_app', 'is_pull_request'], num_rows: 3019 })
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