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https://api.github.com/repos/huggingface/datasets/issues/7523 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/7523/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/7523/comments | https://api.github.com/repos/huggingface/datasets/issues/7523/events | https://github.com/huggingface/datasets/pull/7523 | 2,999,616,692 | PR_kwDODunzps6S1r8w | 7,523 | mention av in video docs | {
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https://api.github.com/repos/huggingface/datasets/issues/7522 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/7522/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/7522/comments | https://api.github.com/repos/huggingface/datasets/issues/7522/events | https://github.com/huggingface/datasets/pull/7522 | 2,998,169,017 | PR_kwDODunzps6SwwXW | 7,522 | Preserve formatting in concatenated IterableDataset | {
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https://api.github.com/repos/huggingface/datasets/issues/7521 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/7521/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/7521/comments | https://api.github.com/repos/huggingface/datasets/issues/7521/events | https://github.com/huggingface/datasets/pull/7521 | 2,997,666,366 | PR_kwDODunzps6SvEZp | 7,521 | fix: Image Feature in Datasets Library Fails to Handle bytearray Objects from Spark DataFrames (#7517) | {
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} | ## Task
Support bytes-like objects (bytes and bytearray) in Features classes
### Description
The `Features` classes only accept `bytes` objects for binary data, but not `bytearray`. This leads to errors when using `IterableDataset.from_spark()` with Spark DataFrames as they contain `bytearray` objects, even though... | null | {
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https://api.github.com/repos/huggingface/datasets/issues/7520 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/7520/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/7520/comments | https://api.github.com/repos/huggingface/datasets/issues/7520/events | https://github.com/huggingface/datasets/issues/7520 | 2,997,422,044 | I_kwDODunzps6yqQfc | 7,520 | Update items in the dataset without `map` | {
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} | null | null | null | ### Feature request
I would like to be able to update items in my dataset without affecting all rows. At least if there was a range option, I would be able to process those items, save the dataset, and then continue.
If I am supposed to split the dataset first, that is not clear, since the docs suggest that any of th... | null | {
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https://api.github.com/repos/huggingface/datasets/issues/7519 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/7519/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/7519/comments | https://api.github.com/repos/huggingface/datasets/issues/7519/events | https://github.com/huggingface/datasets/pull/7519 | 2,996,458,961 | PR_kwDODunzps6Sq76Z | 7,519 | pdf docs fixes | {
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https://api.github.com/repos/huggingface/datasets/issues/7518 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/7518/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/7518/comments | https://api.github.com/repos/huggingface/datasets/issues/7518/events | https://github.com/huggingface/datasets/issues/7518 | 2,996,141,825 | I_kwDODunzps6ylX8B | 7,518 | num_proc parallelization works only for first ~10s. | {
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When I try to load an already downloaded dataset with num_proc=64, the speed is very high for the first 10-20 seconds acheiving 30-40K samples / s, and 100% utilization for all cores but it soon drops to <= 1000 with almost 0% utilization for most cores.
### Steps to reproduce the bug
```
// do... | null | {
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https://api.github.com/repos/huggingface/datasets/issues/7517 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/7517/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/7517/comments | https://api.github.com/repos/huggingface/datasets/issues/7517/events | https://github.com/huggingface/datasets/issues/7517 | 2,996,106,077 | I_kwDODunzps6ylPNd | 7,517 | Image Feature in Datasets Library Fails to Handle bytearray Objects from Spark DataFrames | {
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} | null | null | null | ### Describe the bug
When using `IterableDataset.from_spark()` with a Spark DataFrame containing image data, the `Image` feature class fails to properly process this data type, causing an `AttributeError: 'bytearray' object has no attribute 'get'`
### Steps to reproduce the bug
1. Create a Spark DataFrame with a col... | null | {
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https://api.github.com/repos/huggingface/datasets/issues/7516 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/7516/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/7516/comments | https://api.github.com/repos/huggingface/datasets/issues/7516/events | https://github.com/huggingface/datasets/issues/7516 | 2,995,780,283 | I_kwDODunzps6yj_q7 | 7,516 | unsloth/DeepSeek-R1-Distill-Qwen-32B server error | {
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hfhubhttperror: 500 server error: internal server error for url: https://huggingface.co/api/models/unsloth/deepseek-r1-distill-qwen-32b-bnb-4bit/commits/main (request id: root=1-67fe23fa-3a2150eb444c2a823c388579;de3aed68-c397-4da5-94d4-6565efd3b919) internal error - we're working hard to fix this ... | {
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https://api.github.com/repos/huggingface/datasets/issues/7515 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/7515/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/7515/comments | https://api.github.com/repos/huggingface/datasets/issues/7515/events | https://github.com/huggingface/datasets/issues/7515 | 2,995,082,418 | I_kwDODunzps6yhVSy | 7,515 | `concatenate_datasets` does not preserve Pytorch format for IterableDataset | {
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When concatenating datasets with `concatenate_datasets`, I would expect the resulting combined dataset to be in the same format as the inputs (assuming it's consistent). This is indeed the behavior when combining `Dataset`, but not when combining `IterableDataset`. Specifically, when applying `con... | null | {
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https://api.github.com/repos/huggingface/datasets/issues/7514 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/7514/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/7514/comments | https://api.github.com/repos/huggingface/datasets/issues/7514/events | https://github.com/huggingface/datasets/pull/7514 | 2,994,714,923 | PR_kwDODunzps6Sk7Et | 7,514 | Do not hash `generator` in `BuilderConfig.create_config_id` | {
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https://api.github.com/repos/huggingface/datasets/issues/7513 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/7513/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/7513/comments | https://api.github.com/repos/huggingface/datasets/issues/7513/events | https://github.com/huggingface/datasets/issues/7513 | 2,994,678,437 | I_kwDODunzps6yfyql | 7,513 | MemoryError while creating dataset from generator | {
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"followers_url": "https://api.github.com/use... | [] | open | false | null | [] | null | 3 | 2025-04-15T01:02:02 | 2025-04-15T17:49:39 | null | NONE | null | {
"total": 0,
"completed": 0,
"percent_completed": 0
} | null | null | null | ### Describe the bug
# TL:DR
`Dataset.from_generator` function passes all of its arguments to `BuilderConfig.create_config_id`, including `generator` function itself. `BuilderConfig.create_config_id` function tries to hash all the args, which can take a large amount of time or even cause MemoryError if the dataset pr... | null | {
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https://api.github.com/repos/huggingface/datasets/issues/7512 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/7512/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/7512/comments | https://api.github.com/repos/huggingface/datasets/issues/7512/events | https://github.com/huggingface/datasets/issues/7512 | 2,994,043,544 | I_kwDODunzps6ydXqY | 7,512 | .map() fails if function uses pyvista | {
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"url": "https://api.github.com/users/el-hult",
"html_url": "https://github.com/el-hult",
"followers_url": "https://api.github.com/users/el-hul... | [] | open | false | null | [] | null | 1 | 2025-04-14T19:43:02 | 2025-04-14T20:01:53 | null | NONE | null | {
"total": 0,
"completed": 0,
"percent_completed": 0
} | null | null | null | ### Describe the bug
Using PyVista inside a .map() produces a crash with `objc[78796]: +[NSResponder initialize] may have been in progress in another thread when fork() was called. We cannot safely call it or ignore it in the fork() child process. Crashing instead. Set a breakpoint on objc_initializeAfterForkError to ... | null | {
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https://api.github.com/repos/huggingface/datasets/issues/7510 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/7510/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/7510/comments | https://api.github.com/repos/huggingface/datasets/issues/7510/events | https://github.com/huggingface/datasets/issues/7510 | 2,992,131,117 | I_kwDODunzps6yWEwt | 7,510 | Incompatibile dill version (0.3.9) in datasets 2.18.0 - 3.5.0 | {
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"url": "https://api.github.com/users/JGrel",
"html_url": "https://github.com/JGrel",
"followers_url": "https://api.github.com/users/JGrel/followers",
... | [] | open | false | null | [] | null | 3 | 2025-04-14T07:22:44 | 2025-04-16T09:30:16 | null | NONE | null | {
"total": 0,
"completed": 0,
"percent_completed": 0
} | null | null | null | ### Describe the bug
Datasets 2.18.0 - 3.5.0 has a dependency on dill < 0.3.9. This causes errors with dill >= 0.3.9.
Could you please take a look into it and make it compatible?
### Steps to reproduce the bug
1. Install setuptools >= 2.18.0
2. Install dill >=0.3.9
3. Run pip check
4. Output:
ERROR: pip's dependenc... | null | {
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https://api.github.com/repos/huggingface/datasets/issues/7509 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/7509/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/7509/comments | https://api.github.com/repos/huggingface/datasets/issues/7509/events | https://github.com/huggingface/datasets/issues/7509 | 2,991,484,542 | I_kwDODunzps6yTm5- | 7,509 | Dataset uses excessive memory when loading files | {
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"html_url": "https://github.com/avishaiElmakies",
"followers_url": "https://api... | [] | open | false | null | [] | null | 9 | 2025-04-13T21:09:49 | 2025-04-16T16:49:10 | null | NONE | null | {
"total": 0,
"completed": 0,
"percent_completed": 0
} | null | null | null | ### Describe the bug
Hi
I am having an issue when loading a dataset.
I have about 200 json files each about 1GB (total about 215GB). each row has a few features which are a list of ints.
I am trying to load the dataset using `load_dataset`.
The dataset is about 1.5M samples
I use `num_proc=32` and a node with 378GB of... | null | {
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https://api.github.com/repos/huggingface/datasets/issues/7508 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/7508/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/7508/comments | https://api.github.com/repos/huggingface/datasets/issues/7508/events | https://github.com/huggingface/datasets/issues/7508 | 2,986,612,934 | I_kwDODunzps6yBBjG | 7,508 | Iterating over Image feature columns is extremely slow | {
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"avatar_url": "https://avatars.githubusercontent.com/u/11831521?v=4",
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"url": "https://api.github.com/users/sohamparikh",
"html_url": "https://github.com/sohamparikh",
"followers_url": "https://api.github.com/... | [] | open | false | null | [] | null | 2 | 2025-04-10T19:00:54 | 2025-04-15T17:57:08 | null | NONE | null | {
"total": 0,
"completed": 0,
"percent_completed": 0
} | null | null | null | We are trying to load datasets where the image column stores `PIL.PngImagePlugin.PngImageFile` images. However, iterating over these datasets is extremely slow.
What I have found:
1. It is the presence of the image column that causes the slowdown. Removing the column from the dataset results in blazingly fast (as expe... | null | {
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https://api.github.com/repos/huggingface/datasets/issues/7507 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/7507/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/7507/comments | https://api.github.com/repos/huggingface/datasets/issues/7507/events | https://github.com/huggingface/datasets/issues/7507 | 2,984,309,806 | I_kwDODunzps6x4PQu | 7,507 | Front-end statistical data quantity deviation | {
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"avatar_url": "https://avatars.githubusercontent.com/u/88258534?v=4",
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"url": "https://api.github.com/users/rangehow",
"html_url": "https://github.com/rangehow",
"followers_url": "https://api.github.com/users/ran... | [] | open | false | null | [] | null | 1 | 2025-04-10T02:51:38 | 2025-04-15T12:54:51 | null | NONE | null | {
"total": 0,
"completed": 0,
"percent_completed": 0
} | null | null | null | ### Describe the bug
While browsing the dataset at https://huggingface.co/datasets/NeuML/wikipedia-20250123, I noticed that a dataset with nearly 7M entries was estimated to be only 4M in size—almost half the actual amount. According to the post-download loading and the dataset_info (https://huggingface.co/datasets/Ne... | null | {
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https://api.github.com/repos/huggingface/datasets/issues/7506 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/7506/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/7506/comments | https://api.github.com/repos/huggingface/datasets/issues/7506/events | https://github.com/huggingface/datasets/issues/7506 | 2,981,687,450 | I_kwDODunzps6xuPCa | 7,506 | HfHubHTTPError: 429 Client Error: Too Many Requests for URL when trying to access Fineweb-10BT on 4A100 GPUs using SLURM | {
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"node_id": "MDQ6VXNlcjY2MjAyNTU1",
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"html_url": "https://github.com/calvintanama",
"followers_url": "https://api.github.c... | [] | open | false | null | [] | null | 1 | 2025-04-09T06:32:04 | 2025-04-15T13:04:31 | null | NONE | null | {
"total": 0,
"completed": 0,
"percent_completed": 0
} | null | null | null | ### Describe the bug
I am trying to run some finetunings on 4 A100 GPUs using SLURM using axolotl training framework which in turn uses Huggingface's Trainer and Accelerate on [Fineweb-10BT](https://huggingface.co/datasets/HuggingFaceFW/fineweb), but I end up running into 429 Client Error: Too Many Requests for URL er... | null | {
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https://api.github.com/repos/huggingface/datasets/issues/7505 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/7505/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/7505/comments | https://api.github.com/repos/huggingface/datasets/issues/7505/events | https://github.com/huggingface/datasets/issues/7505 | 2,979,926,156 | I_kwDODunzps6xnhCM | 7,505 | HfHubHTTPError: 403 Forbidden: None. Cannot access content at: https://hf.co/api/s3proxy | {
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"id": 1412262,
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"html_url": "https://github.com/hissain",
"followers_url": "https://api.github.com/users/hissain/... | [] | open | false | null | [] | null | 0 | 2025-04-08T14:08:40 | 2025-04-08T14:08:40 | null | NONE | null | {
"total": 0,
"completed": 0,
"percent_completed": 0
} | null | null | null | I have already logged in Huggingface using CLI with my valid token. Now trying to download the datasets using following code:
from transformers import WhisperProcessor, WhisperForConditionalGeneration, WhisperTokenizer, Trainer, TrainingArguments, DataCollatorForSeq2Seq
from datasets import load_dataset, Data... | null | {
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https://api.github.com/repos/huggingface/datasets/issues/7504 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/7504/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/7504/comments | https://api.github.com/repos/huggingface/datasets/issues/7504/events | https://github.com/huggingface/datasets/issues/7504 | 2,979,410,641 | I_kwDODunzps6xljLR | 7,504 | BuilderConfig ParquetConfig(...) doesn't have a 'use_auth_token' key. | {
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"avatar_url": "https://avatars.githubusercontent.com/u/20015750?v=4",
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"html_url": "https://github.com/tteguayco",
"followers_url": "https://api.github.com/users/... | [] | open | false | null | [] | null | 2 | 2025-04-08T10:55:03 | 2025-04-15T12:36:28 | null | NONE | null | {
"total": 0,
"completed": 0,
"percent_completed": 0
} | null | null | null | ### Describe the bug
Trying to run the following fine-tuning script (based on this page [here](https://github.com/huggingface/instruction-tuned-sd)):
```
! accelerate launch /content/instruction-tuned-sd/finetune_instruct_pix2pix.py \
--pretrained_model_name_or_path=${MODEL_ID} \
--dataset_name=${DATASET_NAME... | null | {
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https://api.github.com/repos/huggingface/datasets/issues/7503 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/7503/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/7503/comments | https://api.github.com/repos/huggingface/datasets/issues/7503/events | https://github.com/huggingface/datasets/issues/7503 | 2,978,512,625 | I_kwDODunzps6xiH7x | 7,503 | Inconsistency between load_dataset and load_from_disk functionality | {
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"followers_url": "https://api.github.com/users/zzzzze... | [] | open | false | null | [] | null | 1 | 2025-04-08T03:46:22 | 2025-04-15T12:39:53 | null | NONE | null | {
"total": 0,
"completed": 0,
"percent_completed": 0
} | null | null | null | ## Issue Description
I've encountered confusion when using `load_dataset` and `load_from_disk` in the datasets library. Specifically, when working offline with the gsm8k dataset, I can load it using a local path:
```python
import datasets
ds = datasets.load_dataset('/root/xxx/datasets/gsm8k', 'main')
```
output:
```t... | null | {
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https://api.github.com/repos/huggingface/datasets/issues/7502 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/7502/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/7502/comments | https://api.github.com/repos/huggingface/datasets/issues/7502/events | https://github.com/huggingface/datasets/issues/7502 | 2,977,453,814 | I_kwDODunzps6xeFb2 | 7,502 | `load_dataset` of size 40GB creates a cache of >720GB | {
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"html_url": "https://github.com/pietrolesci",
"followers_url": "https://api.github.com/... | [] | closed | false | null | [] | null | 2 | 2025-04-07T16:52:34 | 2025-04-15T15:22:12 | 2025-04-15T15:22:11 | NONE | null | {
"total": 0,
"completed": 0,
"percent_completed": 0
} | null | null | null | Hi there,
I am trying to load a dataset from the Hugging Face Hub and split it into train and validation splits. Somehow, when I try to do it with `load_dataset`, it exhausts my disk quota. So, I tried manually downloading the parquet files from the hub and loading them as follows:
```python
ds = DatasetDict(
... | {
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https://api.github.com/repos/huggingface/datasets/issues/7501 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/7501/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/7501/comments | https://api.github.com/repos/huggingface/datasets/issues/7501/events | https://github.com/huggingface/datasets/issues/7501 | 2,976,721,014 | I_kwDODunzps6xbSh2 | 7,501 | Nested Feature raises ArrowNotImplementedError: Unsupported cast using function cast_struct | {
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"followers_url": "https://api.github.com/use... | [] | closed | false | null | [] | null | 1 | 2025-04-07T12:35:39 | 2025-04-07T12:43:04 | 2025-04-07T12:43:03 | NONE | null | {
"total": 0,
"completed": 0,
"percent_completed": 0
} | null | null | null | ### Describe the bug
`datasets.Features` seems to be unable to handle json file that contains fields of `list[dict]`.
### Steps to reproduce the bug
```json
// test.json
{"a": 1, "b": [{"c": 2, "d": 3}, {"c": 4, "d": 5}]}
{"a": 5, "b": [{"c": 7, "d": 8}, {"c": 9, "d": 10}]}
```
```python
import json
from datasets i... | {
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https://api.github.com/repos/huggingface/datasets/issues/7500 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/7500/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/7500/comments | https://api.github.com/repos/huggingface/datasets/issues/7500/events | https://github.com/huggingface/datasets/issues/7500 | 2,974,841,921 | I_kwDODunzps6xUHxB | 7,500 | Make `with_format` correctly indicate that a `Dataset` is compatible with PyTorch's `Dataset` class | {
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} | null | null | null | ### Feature request
Currently `datasets` does not correctly indicate to the Python type-checker (e.g. `pyright` / `Pylance`) that the output of `with_format` is compatible with PyTorch's `Dataloader` since it does not indicate that the HuggingFace `Dataset` is compatible with the PyTorch `Dataset` class. It would be g... | null | {
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https://api.github.com/repos/huggingface/datasets/issues/7499 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/7499/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/7499/comments | https://api.github.com/repos/huggingface/datasets/issues/7499/events | https://github.com/huggingface/datasets/pull/7499 | 2,973,489,126 | PR_kwDODunzps6Rd4Zp | 7,499 | Added cache dirs to load and file_utils | {
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https://api.github.com/repos/huggingface/datasets/issues/7498 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/7498/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/7498/comments | https://api.github.com/repos/huggingface/datasets/issues/7498/events | https://github.com/huggingface/datasets/issues/7498 | 2,969,218,273 | I_kwDODunzps6w-qzh | 7,498 | Extreme memory bandwidth. | {
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} | null | null | null | ### Describe the bug
When I use hf datasets on 4 GPU with 40 workers I get some extreme memory bandwidth of constant ~3GB/s.
However, if I wrap the dataset in `IterableDataset`, this issue is gone and the data also loads way faster (4x faster training on 1 worker).
It seems like the workers don't share memory and b... | null | {
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"total": 0,
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} | null | null | null | ### Feature request
Does someone know how to return the images from videos?
### Motivation
I am trying to use openpi(https://github.com/Physical-Intelligence/openpi) to finetune my Lerobot dataset(V2.0 and V2.1). I find that although the codedaset is v2.0, they are different. It seems like Lerobot V2.0 has two versi... | null | {
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https://api.github.com/repos/huggingface/datasets/issues/7496 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/7496/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/7496/comments | https://api.github.com/repos/huggingface/datasets/issues/7496/events | https://github.com/huggingface/datasets/issues/7496 | 2,967,345,522 | I_kwDODunzps6w3hly | 7,496 | Json builder: Allow features to override problematic Arrow types | {
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} | null | null | null | ### Feature request
In the JSON builder, use explicitly requested feature types before or while converting to Arrow.
### Motivation
Working with JSON datasets is really hard because of Arrow. At the very least, it seems like it should be possible to work-around these problems by explicitly setting problematic colum... | null | {
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https://api.github.com/repos/huggingface/datasets/issues/7495 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/7495/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/7495/comments | https://api.github.com/repos/huggingface/datasets/issues/7495/events | https://github.com/huggingface/datasets/issues/7495 | 2,967,034,060 | I_kwDODunzps6w2VjM | 7,495 | Columns in the dataset obtained though load_dataset do not correspond to the one in the dataset viewer since 3.4.0 | {
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} | null | null | null | ### Describe the bug
I have noticed that on my dataset named [BrunoHays/Accueil_UBS](https://huggingface.co/datasets/BrunoHays/Accueil_UBS), since the version 3.4.0, every column except audio is missing when I load the dataset.
Interestingly, the dataset viewer still shows the correct columns
### Steps to reproduce ... | null | {
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https://api.github.com/repos/huggingface/datasets/issues/7494 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/7494/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/7494/comments | https://api.github.com/repos/huggingface/datasets/issues/7494/events | https://github.com/huggingface/datasets/issues/7494 | 2,965,347,685 | I_kwDODunzps6wv51l | 7,494 | Broken links in pdf loading documentation | {
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} | null | null | null | ### Describe the bug
Hi, just a couple of small issues I ran into while reading the docs for [loading pdf data](https://huggingface.co/docs/datasets/main/en/document_load):
1. The link for the [`Create a pdf dataset`](https://huggingface.co/docs/datasets/main/en/document_load#pdffolder) points to https://huggingface.... | {
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https://api.github.com/repos/huggingface/datasets/issues/7493 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/7493/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/7493/comments | https://api.github.com/repos/huggingface/datasets/issues/7493/events | https://github.com/huggingface/datasets/issues/7493 | 2,964,025,179 | I_kwDODunzps6wq29b | 7,493 | push_to_hub does not upload videos | {
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} | null | null | null | ### Describe the bug
Hello,
I would like to upload a video dataset (some .mp4 files and some segments within them), i.e. rows correspond to subsequences from videos. Videos might be referenced by several rows.
I created a dataset locally and it references the videos and the video readers can read them correctly. I u... | null | {
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https://api.github.com/repos/huggingface/datasets/issues/7492 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/7492/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/7492/comments | https://api.github.com/repos/huggingface/datasets/issues/7492/events | https://github.com/huggingface/datasets/pull/7492 | 2,959,088,568 | PR_kwDODunzps6QtCQM | 7,492 | Closes #7457 | {
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End of preview. Expand in Data Studio
YAML Metadata Warning:The task_ids "token-classification-other-acronym-identification" is not in the official list: acceptability-classification, entity-linking-classification, fact-checking, intent-classification, language-identification, multi-class-classification, multi-label-classification, multi-input-text-classification, natural-language-inference, semantic-similarity-classification, sentiment-classification, topic-classification, semantic-similarity-scoring, sentiment-scoring, sentiment-analysis, hate-speech-detection, text-scoring, named-entity-recognition, part-of-speech, parsing, lemmatization, word-sense-disambiguation, coreference-resolution, extractive-qa, open-domain-qa, closed-domain-qa, news-articles-summarization, news-articles-headline-generation, dialogue-modeling, dialogue-generation, conversational, language-modeling, text-simplification, explanation-generation, abstractive-qa, open-domain-abstractive-qa, closed-domain-qa, open-book-qa, closed-book-qa, text2text-generation, slot-filling, masked-language-modeling, keyword-spotting, speaker-identification, audio-intent-classification, audio-emotion-recognition, audio-language-identification, multi-label-image-classification, multi-class-image-classification, face-detection, vehicle-detection, instance-segmentation, semantic-segmentation, panoptic-segmentation, image-captioning, image-inpainting, image-colorization, super-resolution, grasping, task-planning, tabular-multi-class-classification, tabular-multi-label-classification, tabular-single-column-regression, rdf-to-text, multiple-choice-qa, multiple-choice-coreference-resolution, document-retrieval, utterance-retrieval, entity-linking-retrieval, fact-checking-retrieval, univariate-time-series-forecasting, multivariate-time-series-forecasting, visual-question-answering, document-question-answering, pose-estimation
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