id stringlengths 18 24 | number int64 2 8.48k | title stringlengths 1 290 | body stringlengths 0 228k | state stringclasses 2
values | createdAt timestamp[s]date 2020-04-14 18:18:51 2026-08-13 03:02:44 | updatedAt timestamp[s]date 2020-04-29 09:23:05 2026-08-15 04:47:12 | closedAt timestamp[s]date 2020-04-29 09:23:05 2026-07-28 10:29:56 ⌀ | url stringlengths 48 51 | author dict | labels dict | comments listlengths 0 30 |
|---|---|---|---|---|---|---|---|---|---|---|---|
I_kwDODunzps8AAAABMjWDaQ | 8,475 | `Dataset.select` raises a raw OverflowError on in-range negative indices that its own validation allows | ### Describe the bug
`Dataset.select` validates indices with [`_check_valid_indices_value`](https://github.com/huggingface/datasets/blob/836b82e0544cabf6474b25ade131b4d21e570373/src/datasets/arrow_dataset.py#L636-L638), which implements Python-style negative indexing: it only raises for a negative index when `index + ... | OPEN | 2026-08-13T03:02:44 | 2026-08-13T03:02:44 | null | https://github.com/huggingface/datasets/issues/8475 | {
"login": "codeAnqiang-ma"
} | {
"nodes": []
} | [] |
I_kwDODunzps8AAAABMjUQjw | 8,473 | Negative percent split boundary silently anchors to the start when it rounds to 0 (`train[-1%:]` returns the whole split) | ### Describe the bug
With the default `closest` rounding, a negative percent split boundary whose absolute value rounds to 0 loses its sign, so "relative to the end" silently becomes "relative to the start":
- `train[-1%:]` on a 30-example split returns **all 30 rows** instead of the last 1% (~0 rows, as `train[99%:]... | OPEN | 2026-08-13T02:56:52 | 2026-08-13T02:56:52 | null | https://github.com/huggingface/datasets/issues/8473 | {
"login": "codeAnqiang-ma"
} | {
"nodes": []
} | [] |
I_kwDODunzps8AAAABMa9c9w | 8,472 | batch(0) silently returns one batch with the whole dataset instead of raising | ### Describe the bug
`Dataset.batch()` and `IterableDataset.batch()` accept `batch_size=0` and negative sizes, and quietly return **one batch holding the whole dataset**. Asking for a zero-sized batch produces the largest possible batch, which is as close to the opposite of the request as the API can get.
### Steps o... | OPEN | 2026-08-12T07:52:28 | 2026-08-13T16:29:01 | null | https://github.com/huggingface/datasets/issues/8472 | {
"login": "shashvat-singham"
} | {
"nodes": []
} | [
"Hi @shashvat-singham i did also try and reproduced it and got the same results described :\n\n```text\nIterableDataset.batch(0/-1) → [5]\nDataset.batch(0/-1) → 1 batch\nbatch(2) → [2, 2, 1] / 3 batches\n```\n\nI’d like to give this a try\n\nThanks\n\n#self-assign"
] |
I_kwDODunzps8AAAABMa1yqQ | 8,469 | Empty column loses its dtype under numpy format (always float32) | ### Describe the bug
Under `numpy` format, a column that holds zero rows comes back as `float32` no matter what dtype it was declared with. The same column keeps its dtype as soon as it holds a single row, and the `pandas` and `arrow` formatters keep it in both cases.
This is easy to hit in normal code: any `filter` ... | OPEN | 2026-08-12T07:37:13 | 2026-08-12T07:38:05 | null | https://github.com/huggingface/datasets/issues/8469 | {
"login": "shashvat-singham"
} | {
"nodes": []
} | [] |
I_kwDODunzps8AAAABMau9nQ | 8,467 | PandasArrayExtensionDtype has no construct_from_string, so comparing the dtype to any string raises AssertionError | ### Describe the bug
`PandasArrayExtensionDtype` does not implement `construct_from_string`, so it inherits the base `ExtensionDtype` version, which opens with:
```python
@classmethod
def construct_from_string(cls, string):
assert isinstance(cls.name, str), (cls, type(cls.name))
```
`name` is an instance `@prope... | OPEN | 2026-08-12T07:24:51 | 2026-08-12T07:25:58 | null | https://github.com/huggingface/datasets/issues/8467 | {
"login": "shashvat-singham"
} | {
"nodes": []
} | [] |
I_kwDODunzps8AAAABMaaOWg | 8,465 | PandasArrayExtensionArray.take coerces fill_value before checking whether anything is filled, breaking boolean masks on integer array columns | ### Describe the bug
`PandasArrayExtensionArray.take` coerces `fill_value` to the array's value type **before** checking whether any element will actually be filled:
https://github.com/huggingface/datasets/blob/main/src/datasets/features/features.py#L965-L972
```python
if allow_fill:
fill_value = (
self.... | OPEN | 2026-08-12T06:38:18 | 2026-08-12T06:38:37 | null | https://github.com/huggingface/datasets/issues/8465 | {
"login": "shashvat-singham"
} | {
"nodes": []
} | [] |
I_kwDODunzps8AAAABMZe_1A | 8,463 | very bad quality images in most of them | ### Describe the bug
very bad quality images in most of them
### Steps to reproduce the bug
.
### Expected behavior
.
### Environment info
. | OPEN | 2026-08-12T03:49:23 | 2026-08-12T03:49:23 | null | https://github.com/huggingface/datasets/issues/8463 | {
"login": "anis-mselmi"
} | {
"nodes": []
} | [] |
I_kwDODunzps8AAAABMJnM8A | 8,458 | Replace httpx with httpx2 | ### Feature request
Replace the httpx library with the [httpx2](https://github.com/pydantic/httpx2) fork, maintained by Pydantic.
### Motivation
Httpx has not been released since December 2024, and has closed all public access to Issues / Discussions / PRs, this raises questions about the actual state of maintenance... | OPEN | 2026-08-10T13:01:44 | 2026-08-15T04:47:12 | null | https://github.com/huggingface/datasets/issues/8458 | {
"login": "Aegdesil"
} | {
"nodes": [
{
"name": "enhancement"
}
]
} | [
"Hi @lhoestq can I work on this",
"I think if we would have to discuss in a https://github.com/huggingface/huggingface_hub/ issue about it and `datasets` could align with what's decided there"
] |
I_kwDODunzps8AAAABLwbj6Q | 8,410 | _legacy_no_dict_keys_sorting has no reader since #7817, so the 2.15.0 legacy cache lookup computes the wrong config_id | ### Describe the bug
`Pickler._legacy_no_dict_keys_sorting` has a definition and a writer, but since #7817 it has no reader, so the flag does nothing.
`DatasetBuilder._check_legacy_cache2` patches it on to recompute the `config_id` that 2.15.0 would have produced, because 2.15.0 hashed dicts without sorting their ite... | OPEN | 2026-08-06T18:40:14 | 2026-08-06T18:40:14 | null | https://github.com/huggingface/datasets/issues/8410 | {
"login": "ebarkhordar"
} | {
"nodes": []
} | [] |
I_kwDODunzps8AAAABLaT_hA | 8,394 | IterableDataset.repeat() drops the Arrow fast path and widens numpy dtypes | ### Describe the bug
`RepeatExamplesIterable` is the only wrapper in `iterable_dataset.py` that does not forward `iter_arrow`, `is_typed` and `features` to the iterable it wraps. Two things follow from that: `.repeat()` drops the Arrow fast path, and under `numpy` format it silently widens the declared dtypes.
`SkipE... | OPEN | 2026-08-04T13:01:08 | 2026-08-04T13:01:08 | null | https://github.com/huggingface/datasets/issues/8394 | {
"login": "ebarkhordar"
} | {
"nodes": []
} | [] |
I_kwDODunzps8AAAABLXe4fQ | 8,393 | CPU Bottleneck in `IterableDataset.state_dict()` when shuffling multiple shards | **Describe the bug**
There is a significant CPU bottleneck in `IterableDataset` dataloading when `buffer_size` and `max_buffer_input_shards` are greater than 1 (i.e. highly parallelized streaming with a shuffle buffer).
Currently, `_BaseExamplesIterable.state_dict()` falls back to performing a full recursive `copy.dee... | OPEN | 2026-08-04T07:16:30 | 2026-08-04T07:16:30 | null | https://github.com/huggingface/datasets/issues/8393 | {
"login": "yuxin00j"
} | {
"nodes": []
} | [] |
I_kwDODunzps8AAAABLW1gtA | 8,391 | Nanosecond timestamps are silently truncated even when Value("timestamp[ns]") is requested | ### Describe the bug
`Dataset.from_dict` / `from_list` / `map` silently drop sub-microsecond precision, even when the user explicitly declares a nanosecond feature type. The resulting dataset reports `timestamp[ns]` but the data has already been truncated to microseconds.
### Steps to reproduce the bug
```python
imp... | OPEN | 2026-08-04T05:36:19 | 2026-08-06T02:08:27 | null | https://github.com/huggingface/datasets/issues/8391 | {
"login": "LeSingh1"
} | {
"nodes": []
} | [
"#self-assign"
] |
I_kwDODunzps8AAAABLW1aHQ | 8,390 | to_json cannot round-trip temporal columns: all timestamps written as epoch milliseconds | ### Describe the bug
`Dataset.to_json()` serializes every temporal column as a bare epoch integer at a single fixed resolution (pandas' `date_unit="ms"` default), with no unit recorded in the output. Timestamps therefore do not survive a `to_json` → `from_json` round trip: they either come back silently wrong or raise... | OPEN | 2026-08-04T05:36:00 | 2026-08-10T23:10:37 | null | https://github.com/huggingface/datasets/issues/8390 | {
"login": "LeSingh1"
} | {
"nodes": []
} | [
"#self-assign\n\nOpened a fix in #8459."
] |
I_kwDODunzps8AAAABLWGFhg | 8,386 | map(batched=True, drop_last_batch=True) returns the input unchanged when the dataset is smaller than batch_size | ### Describe the bug
When `drop_last_batch=True` and the dataset is smaller than `batch_size`, `Dataset.map(batched=True, ...)` returns the **input unchanged** instead of an empty dataset. The mapped function is never called, but the original rows are passed through with the original (unbatched) schema.
The iterable ... | OPEN | 2026-08-04T03:21:59 | 2026-08-09T22:06:42 | null | https://github.com/huggingface/datasets/issues/8386 | {
"login": "LeSingh1"
} | {
"nodes": []
} | [] |
I_kwDODunzps8AAAABLS-nkg | 8,381 | IterableDataset.to_dict() and to_polars() return an empty generator instead of the data | ### Describe the bug
`IterableDataset.to_dict()` and `IterableDataset.to_polars()` each have a bare `yield` in their `batched=True` branch, which makes the whole method a generator function. Calling either one the way its docstring shows returns a generator that yields nothing, and the value the `else` branch returns ... | OPEN | 2026-08-03T18:35:13 | 2026-08-03T18:35:25 | null | https://github.com/huggingface/datasets/issues/8381 | {
"login": "ebarkhordar"
} | {
"nodes": []
} | [
"#take"
] |
I_kwDODunzps8AAAABK4yh9Q | 8,375 | `PandasArrayExtensionDtype._metadata` should be a tuple, not a string | ### Describe the bug
There's a small typo in `PandasArrayExtensionDtype` (`src/datasets/features/features.py`):
```python
_metadata = "value_type"
```
Pandas expects `_metadata` to be a tuple of attribute names, like `("value_type",)`, not a plain string ([API documentation ref](https://pandas.pydata.org/docs/refer... | OPEN | 2026-07-31T01:50:02 | 2026-08-12T06:30:29 | null | https://github.com/huggingface/datasets/issues/8375 | {
"login": "kohankhaki"
} | {
"nodes": []
} | [
"#self-assign"
] |
I_kwDODunzps8AAAABKqkD8g | 8,373 | TypeError in _dill.py _batch_setitems with Python 3.14 | ### Describe the bug
When using `load_dataset` on Python 3.14, a `TypeError` is raised during the fingerprinting process inside the bundled `_dill.py`. This happens because Python 3.14 changed the signature of the internal C-level `_Pickler._batch_setitems` to require 3 arguments (`self, items, obj`), while `datasets/... | OPEN | 2026-07-29T15:00:19 | 2026-08-01T19:30:07 | null | https://github.com/huggingface/datasets/issues/8373 | {
"login": "Vinello28"
} | {
"nodes": []
} | [
"Hey Mates, this works: In src/datasets/utils/_dill.py, starting around line 71, update the _batch_setitems overriding to pass the obj argument downstream.\n\n def _batch_setitems(self, items, obj=None):\n if self._legacy_no_dict_keys_sorting:\n return super()._batch_setitems(items,... |
I_kwDODunzps8AAAABKJdn3g | 8,365 | to_json/to_csv/to_sql cast nullable integer columns to float, corrupting values past 2**53 | ### Describe the bug
`Dataset.to_json`, `to_csv`, and `to_sql` write a nullable integer column as floating point rather than integers. All three writers (`io/json.py`, `io/csv.py`, `io/sql.py`) call `batch.to_pandas()` with pyarrow's default `integer_object_nulls=False`, which casts any integer column containing a nul... | CLOSED | 2026-07-25T13:38:01 | 2026-07-28T10:29:56 | 2026-07-28T10:29:56 | https://github.com/huggingface/datasets/issues/8365 | {
"login": "ebarkhordar"
} | {
"nodes": []
} | [] |
I_kwDODunzps8AAAABJ_L-6w | 8,362 | ArrayXD fixed-shape integer column with a null row is silently cast to float on the python read path | ### Describe the bug
A fixed-shape `ArrayXD` column (for example `Array2D(shape=(1, 2), dtype="int64")`) that contains at least one `None` row is silently cast to float on the python read path. `to_dict()` / `to_pylist()` return every value as a float, and integers above 2**53 lose precision, purely because an unrelat... | CLOSED | 2026-07-24T04:32:35 | 2026-07-24T11:59:13 | 2026-07-24T11:59:13 | https://github.com/huggingface/datasets/issues/8362 | {
"login": "ebarkhordar"
} | {
"nodes": []
} | [] |
I_kwDODunzps8AAAABJ-7a3Q | 8,359 | IterableDataset.filter() checkpoint/resume silently drops the rest of the in-flight Arrow table | ### Describe the bug
Resuming a streaming `IterableDataset.filter()` from a `state_dict()` checkpoint silently drops rows: the remainder of the in-flight Arrow table is skipped. For a single-shard dataset this loses up to a full row group per checkpoint, and for a single-table shard it can drop every unconsumed row.
... | CLOSED | 2026-07-24T03:36:32 | 2026-07-24T12:06:21 | 2026-07-24T12:06:21 | https://github.com/huggingface/datasets/issues/8359 | {
"login": "ebarkhordar"
} | {
"nodes": []
} | [
"#self-assign"
] |
I_kwDODunzps8AAAABJ33lPg | 8,351 | with_format('numpy') promotes flat float64/int columns with nulls to dtype=object (float32 stays numeric) | ### Describe the bug
`NumpyArrowExtractor._arrow_array_to_numpy` (used by `Dataset.with_format("numpy")`) promotes a flat, homogeneous numeric column to `dtype=object` when the column contains nulls, but only for `float64`/`int64` columns. A `float32` column is returned as a numeric array. The result is a silent wrong... | CLOSED | 2026-07-23T09:41:06 | 2026-07-23T17:32:25 | 2026-07-23T17:32:25 | https://github.com/huggingface/datasets/issues/8351 | {
"login": "ebarkhordar"
} | {
"nodes": []
} | [] |
I_kwDODunzps8AAAABJU4jRg | 8,343 | Dataset.to_pandas() returns raw JSON strings for Json() columns instead of decoded objects | ### Describe the bug
`Dataset.to_pandas()` returns the raw Arrow storage strings for `Json()` feature columns, while every other in-memory export path decodes them to Python objects. `to_dict()`, `to_list()`, `to_json()` and `with_format("pandas")` all run `get_json_field_paths_from_feature` + `json_decode_field`, but... | CLOSED | 2026-07-19T01:44:53 | 2026-07-24T13:19:08 | 2026-07-24T13:19:08 | https://github.com/huggingface/datasets/issues/8343 | {
"login": "ebarkhordar"
} | {
"nodes": []
} | [] |
I_kwDODunzps8AAAABJR6Akw | 8,341 | concatenate_datasets(axis=1) with Arrow format drops the first source's columns | ### Describe the bug
The Arrow fast path of horizontal concatenation (`concatenate_datasets([...], axis=1)` consumed through `.with_format("arrow")`, or any Arrow/tensor consumer) drops the columns of the first source. The plain-Python path is correct; only the Arrow path diverges.
`HorizontallyConcatenatedMultiSourc... | CLOSED | 2026-07-18T09:41:43 | 2026-07-22T18:35:31 | 2026-07-22T18:35:31 | https://github.com/huggingface/datasets/issues/8341 | {
"login": "ebarkhordar"
} | {
"nodes": []
} | [
"#self-assign"
] |
I_kwDODunzps8AAAABIxjmTA | 8,331 | datasets-server.huggingface.co returning 503 on every endpoint (whole host down, not one route) | ### Describe the bug
The entire datasets-server.huggingface.co backend (the dataset-viewer API) is
returning 503 Service Temporarily Unavailable on every route I've tried, not
just one endpoint. It reproduces on public datasets with no auth token, so it
doesn't appear to be account- or dataset-specific. huggingface.co... | CLOSED | 2026-07-14T13:59:29 | 2026-07-17T12:09:35 | 2026-07-17T12:09:34 | https://github.com/huggingface/datasets/issues/8331 | {
"login": "ChristianDenniss"
} | {
"nodes": []
} | [
"Hi ! Thanks for the ping, yes we are aware of the issue and actively working on it. It's taking some time though since we want to make sure it will be 100% back and for good.\n\nThis impacts both the API and the Viewer on HF which is based on it",
"Seems to be up and running properly now I'll conclude this issue... |
I_kwDODunzps8AAAABIxG3Ww | 8,330 | Dataset Studio and Viewer down | ### Describe the bug
Hello!
I want to report a bug on the datasets viewer and data studio pages. I have attempted to access it on various datasets from various devices and it will not let me view the dataset this way. I have tried restarting, login in and out but to no success. I use Hugging Face as a repository th... | CLOSED | 2026-07-14T13:06:53 | 2026-07-24T15:26:15 | 2026-07-24T15:26:15 | https://github.com/huggingface/datasets/issues/8330 | {
"login": "Taryn-Cail"
} | {
"nodes": []
} | [
"Hi ! Thanks for the ping, yes we are aware of the issue and actively working on it. It's taking some time though since we want to make sure it will be 100% back and for good"
] |
I_kwDODunzps8AAAABIvhOLA | 8,328 | Streaming datasets fail with 403 SignatureError: invalid key pair id from xet-bridge-us (Colab, latest libraries) | ### Describe the bug
I'm unable to stream datasets from the Hugging Face Hub. The issue affects both public datasets (e.g. beans) and gated datasets (ILSVRC/imagenet-1k).
The failure occurs before any examples are yielded. The request is redirected to the Xet CDN (xet-bridge-us) and fails with:
```
403 Forbidden
Au... | CLOSED | 2026-07-14T09:21:43 | 2026-07-24T15:26:24 | 2026-07-24T15:26:24 | https://github.com/huggingface/datasets/issues/8328 | {
"login": "mahmoud-mannes"
} | {
"nodes": []
} | [
"Hi ! I couldn't reproduce the issue on my side. I can see two options, let me know if any helps you:\n\n1) this was a transient issue (we restarted some machines recently but this shouldn't have impacted you tbh), can you try again just in case ?\n2) something is wrong with your token smh, can you logout and login... |
I_kwDODunzps8AAAABIoqexg | 8,327 | `Dataset.from_pandas` allocates ~1 MB per Arrow chunk, Out of Memory errors | ### Describe the bug
`Dataset.from_pandas` memory usage scales with the chunk count of the backing Arrow array (around 1 MB per chunk).
`Dataset.shuffle()` followed by `to_pandas()` produces string columns with one chunk per row, so a 25k-row DataFrame holding ~32 MB of text allocates ~30 GB on the way back through ... | CLOSED | 2026-07-13T14:13:38 | 2026-07-22T17:28:51 | 2026-07-22T17:28:51 | https://github.com/huggingface/datasets/issues/8327 | {
"login": "nenadom"
} | {
"nodes": []
} | [
"The measurements in the issue point at `from_pandas`, but I think the allocation is actually in fingerprinting, and not in the Arrow conversion at all.\n\nOn datasets 5.0.0 I get:\n\n| step | peak |\n|---|---|\n| `pa.Table.from_pandas(df)` | ~0 MB |\n| `Dataset.from_pandas(df)` | 1499 MB |\n| `generate_fingerprint... |
I_kwDODunzps8AAAABIiJwaQ | 8,324 | Path traversal / arbitrary file read via the `file_name` metadata field in `*folder` dataset builders (no `trust_remote_code`) | ### Describe the bug
reported via email on 9 June 2026 - no acknowledgement or response:
Package: datasets (PyPI). Affected file: src/datasets/packaged_modules/folder_based_builder/folder_based_builder.py
Affected Versions: confirmed on 5.0.0 (PyPI) and HEAD 63e103e.
CVSS: CVSS:3.1/AV:N/AC:L/PR:N/UI:R/S:U/C:H/I:N/A:N... | CLOSED | 2026-07-12T15:38:21 | 2026-07-23T15:37:57 | 2026-07-23T15:37:57 | https://github.com/huggingface/datasets/issues/8324 | {
"login": "geo-chen"
} | {
"nodes": []
} | [
"#self-assign"
] |
I_kwDODunzps8AAAABHy6FNw | 8,308 | Streaming IterableDataset state stops advancing after first resume — second resume restarts from the beginning |
## Description
For a streaming `IterableDataset`, calling `load_state_dict()` and then continuing to iterate leaves `state_dict()` frozen at the initial position (`shard_idx=0`, `shard_example_idx=0`). Reading resumes correctly the first time, but the tracked state never advances again.
This causes a second consecut... | CLOSED | 2026-07-06T10:12:27 | 2026-07-24T07:58:49 | 2026-07-23T13:12:33 | https://github.com/huggingface/datasets/issues/8308 | {
"login": "francesco-bertolotti"
} | {
"nodes": []
} | [
"@francesco-bertolotti Hi maintainers! I am an NLP intern at Sunbird AI and a first-time contributor. I would love to work on this issue. Could you please assign it to me?",
"Thank you for your interest @SsemuliJoseph \n\nThe fix was merged 2 weeks ago https://github.com/huggingface/datasets/pull/8295\nI should p... |
I_kwDODunzps8AAAABHmFpKA | 8,302 | Turkish DIK-style Syntactic Structure Benchmark Dataset | ### Feature request
A structured dataset proposal introducing a Turkish syntactic structure benchmark designed for evaluating LLMs on fine-grained grammatical reasoning in a morphologically rich language.
Current NLP datasets in Hugging Face focus heavily on surface-level semantic tasks or English-centric benchmarks.... | OPEN | 2026-07-03T15:33:39 | 2026-08-09T12:19:58 | null | https://github.com/huggingface/datasets/issues/8302 | {
"login": "nane100503-gif"
} | {
"nodes": [
{
"name": "enhancement"
}
]
} | [
"Hi! I'd be interested in helping with this benchmark. I have experience working with NLP datasets and Hugging Face tooling, and I'd be happy to contribute on the engineering side (dataset packaging, loading script, validation, documentation, evaluation utilities, or testing). If you're planning to move forward, I'... |
I_kwDODunzps8AAAABHOI25g | 8,296 | [security] Symlink-Following Arbitrary File Write via Archive Extraction in huggingface/datasets | ### Describe the bug
## Summary
A symlink-following vulnerability exists in the archive extraction subsystem of `huggingface/datasets` that allows a local attacker with write access to a shared HuggingFace cache directory to write arbitrary files with the victim's privileges, by pre-planting a symlink at a predictabl... | OPEN | 2026-06-30T18:46:34 | 2026-07-04T19:06:53 | null | https://github.com/huggingface/datasets/issues/8296 | {
"login": "AAtomical"
} | {
"nodes": []
} | [
"thanks for reporting, I'm not entirely sure how someone could exploit this but a fix would be welcome for sure ! Option A looks good to me",
"@lhoestq Thanks for the quick response! I opened a PR #8303 implementing Option A. The threat model is a shared cache. Any user who can write into downloads/extracted/ — b... |
I_kwDODunzps8AAAABHI57og | 8,293 | Support concatenating multiple streaming datasets while preserving the sum of shards | ### Feature request
It would be useful if concatenating multiple `IterableDataset`s could preserve the shard information from each input dataset, so that:
- the total number of shards equals the sum of the input shards;
- `split_dataset_by_node()` and worker sharding continue to work efficiently;
- downstream distrib... | OPEN | 2026-06-30T05:44:23 | 2026-07-03T13:40:43 | null | https://github.com/huggingface/datasets/issues/8293 | {
"login": "muyihao"
} | {
"nodes": [
{
"name": "enhancement"
}
]
} | [
"it's already the case afaik:\n\n```python\nIn [1]: from datasets import IterableDataset, concatenate_datasets\n\nIn [2]: ds1 = IterableDataset.from_dict({\"i\": [0, 1]})\n\nIn [3]: ds2 = IterableDataset.from_dict({\"i\": [2, 3]})\n\nIn [4]: ds = concatenate_datasets([ds1, ds2])\n\nIn [5]: list(ds)\nOut[5]: [{'i': ... |
I_kwDODunzps8AAAABFaF9XA | 8,269 | MetadataConfigs drops parquet shards when exported config rows are non-consecutive | ## Bug
`_from_exported_parquet_files_and_dataset_infos()` uses `itertools.groupby()` on unsorted `exported_parquet_files`.
If the same `config` appears again after another config, the earlier shard URLs are lost.
## Repro
```python
from itertools import groupby
from operator import itemgetter
exported = [
{"co... | OPEN | 2026-06-14T04:07:09 | 2026-06-14T04:07:09 | null | https://github.com/huggingface/datasets/issues/8269 | {
"login": "KirtiRamchandani"
} | {
"nodes": []
} | [] |
I_kwDODunzps8AAAABFREIKQ | 8,261 | Feature Proposal: Add FunASR Chinese/Multilingual ASR Benchmark Datasets | <!-- funasr-ops:accuracy-note-20260714 -->
> [!NOTE]
> **License and capability clarification (2026-07-14):** FunASR is a toolkit, not a single checkpoint. The [FunASR](https://github.com/modelscope/FunASR#license) and [SenseVoice](https://github.com/FunAudioLLM/SenseVoice#license) repository source code is MIT; model ... | OPEN | 2026-06-12T10:23:14 | 2026-07-14T05:32:24 | null | https://github.com/huggingface/datasets/issues/8261 | {
"login": "LauraGPT"
} | {
"nodes": []
} | [] |
I_kwDODunzps8AAAABE9PTZA | 8,256 | Dataset Viewer fails on TSFile datasets | ### Describe the bug
## Description
The Dataset Viewer fails when trying to display a dataset stored in TSFile format.
The error shown by the viewer is:
```python
ModuleNotFoundError: No module named 'tsfile'
### Steps to reproduce the bug
# Dataset Viewer fails to load TSFile dataset due to missing `tsfile` depe... | OPEN | 2026-06-10T03:15:32 | 2026-07-06T01:52:51 | null | https://github.com/huggingface/datasets/issues/8256 | {
"login": "gengziyand"
} | {
"nodes": []
} | [
"Thanks for reporting ! I'm working on it :)\n\nThe viewer doesn't use `datasets` V5 yet, I have to do some minor adjustments first",
"I opened a PR that addresses the missing optional tsfile dependency error by replacing the raw ModuleNotFoundError with a clearer ImportError and adding a regression test.\n\nThis... |
I_kwDODunzps8AAAABE0gLAw | 8,253 | Feature request: Add a streaming_shard operator for early sample-level sharding when file-level sharding is insufficient | ## Feature request: Add a streaming_shard operator for early sample-level sharding when file-level sharding is insufficient
### Proposed API
It would be useful to provide a first-class streaming sharding operator in `datasets`, for example:
```python
dataset = datasets.load_dataset(..., streaming=True, split="train"... | OPEN | 2026-06-09T03:14:46 | 2026-06-29T13:00:36 | null | https://github.com/huggingface/datasets/issues/8253 | {
"login": "muyihao"
} | {
"nodes": [
{
"name": "enhancement"
}
]
} | [
"I feel like IterableDatasetShard is not well suited for this and shouldn't be used / should be improved. Instead there is `ds.shard()` or even `split_dataset_by_node()` which works when `num_physical_files < global_world_size`. WDYT ?",
"I checked current `main`, and the requested behavior seems to sit between t... |
I_kwDODunzps8AAAABEprXCA | 8,247 | VORTEXRAG benchmarked on 6 HuggingFace datasets — new open-source RAG framework | Hi HuggingFace Datasets team!
**VORTEXRAG** was evaluated on 6 datasets available on the HuggingFace Hub using datasets.load_dataset():
- NQ, TriviaQA, WebQ, PopQA, HotpotQA, 2WikiMultiHopQA
Results: EM 74.8, F1 82.6 averaged across all 6. Full evaluation code is in the repo.
- GitHub: https://github.com/vignesh202... | OPEN | 2026-06-07T11:14:50 | 2026-06-07T11:14:50 | null | https://github.com/huggingface/datasets/issues/8247 | {
"login": "vignesh2027"
} | {
"nodes": []
} | [] |
I_kwDODunzps8AAAABEpG_1w | 8,246 | RecursionError when loading GLB file with deeply nested JSON in Mesh feature | ## Description
Loading a GLB file with deeply nested JSON chunk causes a RecursionError, crashing the application.
## Step to Reproduce
```python
from datasets import Dataset, Mesh
import tempfile, os, struct
def make_malicious_glb(depth=5000):
json_chunk = (b'{"a":' * depth + b'1' + b'}' * depth)
magic = b... | OPEN | 2026-06-07T07:10:22 | 2026-08-12T06:46:48 | null | https://github.com/huggingface/datasets/issues/8246 | {
"login": "BeyondBirthday07"
} | {
"nodes": []
} | [
"#self-assign"
] |
I_kwDODunzps8AAAABEiAVMA | 8,242 | "eval_strategy": "no" perform evaluation | ### Describe the bug
Hi,
I'm trying to train a diffusion model and I getting stuck with
```
strace -p 967873
strace: Process 967873 attached
ioctl(9, _IOC(_IOC_READ|_IOC_WRITE, 0x46, 0x2a, 0x20), 0x7fff18579d90) = 0
ioctl(9, _IOC(_IOC_READ|_IOC_WRITE, 0x46, 0x2a, 0x20), 0x7fff18579d90) = 0
```
But my issue is that ... | OPEN | 2026-06-05T18:08:17 | 2026-06-20T14:48:43 | null | https://github.com/huggingface/datasets/issues/8242 | {
"login": "SamuelLarkin"
} | {
"nodes": []
} | [
"Wrong repo, this belongs in axolotl, not `datasets`. And `eval_strategy: \"no\"` was never going to stop it.\n\nWhat hangs you is the diffusion plugin's sample generation. `DiffusionGenerationCallback.on_step_end` fires on `global_step % generation_interval == 0` and ignores `eval_strategy`. When you have no eval ... |
I_kwDODunzps8AAAABEgwy_Q | 8,241 | load_dataset("json", ...) infers a different schema when the JSONL file starts with a UTF-8 BOM | ### Describe the bug
When a JSONL file starts with a UTF-8 BOM (`\xef\xbb\xbf`), `datasets.load_dataset("json", data_files=...)` infers a different schema than when the same file is loaded without the BOM. Specifically, the loader's "mixed-struct-types" pre-scan — which normally promotes columns with heterogeneous nes... | CLOSED | 2026-06-05T14:39:46 | 2026-06-09T15:48:27 | 2026-06-09T15:48:27 | https://github.com/huggingface/datasets/issues/8241 | {
"login": "f-salvetti"
} | {
"nodes": []
} | [
"#self-assign"
] |
I_kwDODunzps8AAAABDFJofw | 8,217 | Multi-GPU Training with Large Dataset — NCCL Timeouts / Slow Data Loading + Excessive Memory Usage with keep_in_memory=True | Hi, I'm training a large dataset using Lerobot (which relies on Hugging Face Datasets) and encountering severe performance issues when scaling to multi-GPU training.
### Problem Description
- Unstable/slow data loading + NCCL timeouts
- Step time fluctuates drastically: ~1s/step (fast) vs ~45s/step (extremely slow)
... | CLOSED | 2026-05-22T09:55:13 | 2026-06-03T02:12:43 | 2026-06-03T02:12:43 | https://github.com/huggingface/datasets/issues/8217 | {
"login": "D222097"
} | {
"nodes": []
} | [
"Hi @D222097,\n\nWe have audited the architectural footprint of your multi-GPU training setup. The behaviors you are experiencing are not bugs within the `datasets` library, but rather fundamental limitations of Python's process architecture interacting with hardware topologies. \n\nHere is the clinical breakdown o... |
I_kwDODunzps8AAAABCdZ3ew | 8,204 | Please enable Private Vulnerability Reporting | Hi datasets team,
I have a security finding in datasets that I would like to disclose privately. GitHub Private Vulnerability Reporting is currently disabled on this repo.
Could you turn it on? It's at Settings > Security > Code security and analysis > Private vulnerability reporting. Once enabled I will file the ful... | OPEN | 2026-05-16T13:28:01 | 2026-05-16T13:28:01 | null | https://github.com/huggingface/datasets/issues/8204 | {
"login": "0xBassia"
} | {
"nodes": []
} | [] |
I_kwDODunzps8AAAABCZ9hOA | 8,201 | Encountered an error when loading data in WebDataset format using `load_datasets` during multi-matchines training. | ### Describe the bug
Single-machine training works fine, but multi-machine training throws up all sorts of weird bugs. Help me!
### Steps to reproduce the bug
train_dataset = load_dataset(
"webdataset", data_files=args.train_dataset, split="train", streaming=True,cache_dir='/dev/shm/.cache'
)
args.train... | OPEN | 2026-05-15T19:21:24 | 2026-05-20T12:58:57 | null | https://github.com/huggingface/datasets/issues/8201 | {
"login": "aihao2000"
} | {
"nodes": []
} | [
"Hi @aihao2000 ! I was looking into this multi-machine training scenario and just opened a PR (#8203 ) that safely skips feature inference for empty shards during distributed streaming.\n\nplease! Check it out and see if it looks like it will resolve the weird bugs you were hitting!",
"it looks like there less da... |
I_kwDODunzps8AAAABCZXobQ | 8,199 | Replace AutoFeatureExtractor with AutoImageProcessor in image preprocessing docs | ## Summary
The `docs/source/use_dataset.mdx` documentation uses `AutoFeatureExtractor` from `transformers` in its image preprocessing example. For vision models, `AutoImageProcessor` is now the recommended API and better reflects current `transformers` conventions.
## Problem
In the [[Apply data augmentations](https... | CLOSED | 2026-05-15T17:34:53 | 2026-07-22T17:35:56 | 2026-07-22T17:35:56 | https://github.com/huggingface/datasets/issues/8199 | {
"login": "ajaystar8"
} | {
"nodes": []
} | [
"I'd like to work on this. I'll open a PR shortly."
] |
I_kwDODunzps8AAAABCV-Bqw | 8,197 | Feature Request / Discussion: Skip origin_metadata fetch when streaming=True? | Hi team!
I've been looking into the initialization process of the `DatasetBuilder` and noticed that the ETag/origin metadata caching path is executed unconditionally.
While fetching the `origin_metadata` and calculating the ETag is necessary for safely managing a local disk cache when using `as_dataset()`, it seems t... | OPEN | 2026-05-15T07:43:57 | 2026-06-17T03:39:14 | null | https://github.com/huggingface/datasets/issues/8197 | {
"login": "yuxin00j"
} | {
"nodes": []
} | [
"I think it's great that it checks that every file does exist by default. It's relatively cheap since it uses fsspec which caches file info at folder level.\n\nOn the other hand why not add skip_origin_metadata=False from @TheDerbiedOne by default to DatasetBuilder and document what it does (load_dataset passes kwa... |
I_kwDODunzps8AAAABBhmhxw | 8,178 | The full dataset viewer is not available (click to read why). Only showing a preview of the rows. Job manager crashed while running this job (missing heartbeats). Error code: JobManagerCrashedError | ### Describe the bug
The full dataset viewer is not available (click to read why). Only showing a preview of the rows.
Job manager crashed while running this job (missing heartbeats).
Error code: JobManagerCrashedError
see: https://huggingface.co/datasets/Genius-Society/tt100k/viewer
### Steps to reproduce the bug... | OPEN | 2026-05-07T08:33:48 | 2026-05-31T00:09:38 | null | https://github.com/huggingface/datasets/issues/8178 | {
"login": "kakamond"
} | {
"nodes": []
} | [
"Oh yeah, we hit something pretty similar when running a dataset viewer on a large collection (~3M rows) a few months back. The JobManagerCrashedError with missing heartbeats usually showed up for us when the server process ran out of memory or couldn’t keep up with the load spikes during dataset streaming. Turns o... |
I_kwDODunzps8AAAABBOHifA | 8,171 | Dataset UI shows 0:00/0:00 for audio after push_to_hub | I’m seeing an issue where audio previews in the dataset viewer show `0:00/0:00` after uploading with push_to_hub.
## What I did
I tried to avoid `torchcodec` because I want to keep the packages small using the following code:
```python
import io
import os
import shutil
import tempfile
from pathlib import Path
imp... | CLOSED | 2026-05-04T13:17:25 | 2026-05-20T10:46:58 | 2026-05-20T10:46:58 | https://github.com/huggingface/datasets/issues/8171 | {
"login": "MNIKIEMA"
} | {
"nodes": []
} | [
"Hello,\nI am trying to find my first issue to resolve. I can't reproduce your problem. When I go in the hub UI to your dataset. I can see the length of each audio. It takes some time to load \n\n## Dataset Card\n<img width=\"584\" height=\"644\" alt=\"Image\" src=\"https://github.com/user-attachments/assets/8b0e38... |
I_kwDODunzps8AAAABBEPO0g | 8,169 | Streaming dataset hangs consistently | ### Describe the bug
When loading a dataset with `streaming=True`, some background process prevents the script from ever returning (or at least for a very long time).
This did not happen with `huggingface-hub < 1`.
### Steps to reproduce the bug
from datasets import load_dataset
ds = load_dataset("IRIIS-RESEARCH/N... | CLOSED | 2026-05-01T20:27:58 | 2026-05-06T16:07:04 | 2026-05-06T16:06:08 | https://github.com/huggingface/datasets/issues/8169 | {
"login": "michaelpginn"
} | {
"nodes": []
} | [
"+1 also encountered",
"I pushed a workaround for the current version of PyArrow (24.0.0) and older versions at https://github.com/huggingface/datasets/pull/8176\n\nFor future versions it should be fixed directly in PyArrow"
] |
I_kwDODunzps8AAAABA62Vtw | 8,167 | [BUG] Abnormal progress bar in dataset.map when load_from_cache_file=False | ### Describe the bug
datasets 4.8.5
```python
from datasets import load_dataset, load_from_disk
data = load_from_disk('pretrain_cached_dataset/train')
def dummy_map(example):
return example
dataset = data.map(dummy_map)
dataset = data.map(dummy_map, load_from_cache_file=True) ... | CLOSED | 2026-04-30T08:47:53 | 2026-05-29T10:59:07 | 2026-05-29T10:59:07 | https://github.com/huggingface/datasets/issues/8167 | {
"login": "Jintao-Huang"
} | {
"nodes": []
} | [
"https://github.com/huggingface/datasets/blob/4e3bf52ff436d841e61211dfa096b5c47197ae36/src/datasets/arrow_dataset.py#L3593-L3598",
"Hi, can you provide more details on the issue ?",
"<img width=\"340\" height=\"26\" alt=\"Image\" src=\"https://github.com/user-attachments/assets/0dca6f47-4a8d-4871-a908-f58df856e... |
I_kwDODunzps8AAAABA5ItqQ | 8,165 | IterableDataset: corrupted EXIF image silently terminates streaming iterator instead of skipping the sample | ## Summary
When iterating over a streaming `IterableDataset` that contains images with corrupted EXIF metadata (e.g., a TIFF rational tag with denominator=0), PIL raises `ZeroDivisionError` inside `exif_transpose`. This exception propagates through the HuggingFace `datasets` pipeline and **terminates the streaming ite... | OPEN | 2026-04-30T02:20:54 | 2026-07-13T15:57:08 | null | https://github.com/huggingface/datasets/issues/8165 | {
"login": "LIUYellowBlack"
} | {
"nodes": []
} | [
"Hi ! Would it be acceptable to return None instead of skipping ? This way we can provide the same API for non-streaming (since the length of the dataset is known in advance and fixed). Then a subsequent .filter call can take care of skipping the samples. Something like this maybe ?\n\n```python\nds = load_dataset(... |
I_kwDODunzps8AAAABA5FcPQ | 8,164 | Lance: HF auth token dropped for private repos in streaming mode (broken `storage_options` lookup) | ### Describe the bug
When `Lance._split_generators` receives `hf://` URIs - i.e. anywhere a `StreamingDownloadManager` is in play (`load_dataset(..., streaming=True)`, `get_dataset_split_names`, and the dataset-viewer worker) - the HF auth token is silently dropped before reaching `lance.dataset(...)`. Lance then atte... | CLOSED | 2026-04-30T02:03:33 | 2026-04-30T15:38:43 | 2026-04-30T15:38:43 | https://github.com/huggingface/datasets/issues/8164 | {
"login": "ericjaebeom"
} | {
"nodes": []
} | [
"I can see the fix. Changing `split(\"://\", 0)` to `split(\"://\", 1)` and removing the `+ \"://\"` suffix. The key lookup should be `\"hf\"` not `\"hf://\"`. \nI'd like to submit a PR for this. Is this still open?",
"Well, I am already writing a PR for this, and it is just about to be submitted."
] |
End of preview. Expand in Data Studio
GitHub Issues Dataset
Dataset Description
The GitHub Issues Dataset is a collection of publicly
available GitHub issues collected from the
Hugging Face datasets repository.
Each example represents a GitHub issue and contains information such as the issue identifier, issue number, title, description, state, timestamps, author, labels, original URL, and comments.
The dataset was collected using the GitHub GraphQL API with cursor-based pagination.
The dataset is intended for research and experimentation in Natural Language Processing (NLP), software engineering, information retrieval, semantic search, issue analysis, question answering, and Large Language Models (LLMs).
Dataset Details
- Source: Hugging Face
datasetsrepository - Source platform: GitHub
- Domain: Software development
- Language: Primarily English
- Data type: Text and structured metadata
- Number of examples: 3,343
- Format: Parquet / Arrow
- Split:
train
Source
The original data was collected from the public GitHub repository:
https://github.com/huggingface/datasets
The original issues are available through the GitHub Issues section of the repository.
Data Collection
The dataset was collected through the GitHub GraphQL API.
Cursor-based pagination was used to retrieve issues from the repository.
For each issue, the following information was collected:
- Issue ID
- Issue number
- Title
- Body
- State
- Creation timestamp
- Update timestamp
- Closing timestamp
- Original GitHub URL
- Author login
- Labels
- Comments
Only publicly accessible information was collected.
Dataset Structure
Each example contains the following fields:
| Field | Type | Description |
|---|---|---|
id |
string | Unique GitHub identifier for the issue |
number |
int64 | GitHub issue number |
title |
string | Title of the issue |
body |
string | Main description and content of the issue |
state |
string | Current issue state, such as OPEN or CLOSED |
createdAt |
timestamp | Date and time when the issue was created |
updatedAt |
timestamp | Date and time when the issue was last updated |
closedAt |
timestamp | Date and time when the issue was closed, if applicable |
url |
string | Original GitHub issue URL |
author |
struct | Information about the issue author |
labels |
struct | Labels assigned to the issue |
comments |
list[string] | Comments associated with the issue |
Example
A simplified example of a dataset record:
{
"id": "I_kwDODunzps8AAAABMjWDaQ",
"number": 8475,
"title": "Dataset.select raises a raw OverflowError on in-range negative indices",
"body": "Describe the bug ...",
"state": "OPEN",
"createdAt": "2026-08-13T03:02:44",
"updatedAt": "2026-08-13T03:02:44",
"closedAt": null,
"url": "https://github.com/huggingface/datasets/issues/8475",
"author": {
"login": "codeAnqiang-ma"
},
"labels": {
"nodes": []
},
"comments": []
}
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