the raw data for our processed PythonEdu-Rs dataset, adopted from the original dataset from HuggingFaceTB team. The data format for each line in the 0368500filteredv2ds25.sced.jsonl is as follows: "problemdescription"
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Updated 2026-09-18 · How the library is built
859 datasets, sorted by most downloaded.
the raw data for our processed PythonEdu-Rs dataset, adopted from the original dataset from HuggingFaceTB team. The data format for each line in the 0368500filteredv2ds25.sced.jsonl is as follows: "problemdescription"
the raw data for our processed PythonEdu-Rs dataset, adopted from the original dataset from HuggingFaceTB team. The data format for each line in the 0368500filteredv2ds25.sced.jsonl is as follows: "problemdescription"
the raw data for our processed PythonEdu-Rs dataset, adopted from the original dataset from HuggingFaceTB team. The data format for each line in the 0368500filteredv2ds25.sced.jsonl is as follows: "problemdescription"
the raw data for our processed PythonEdu-Rs dataset, adopted from the original dataset from HuggingFaceTB team. The data format for each line in the 0368500filteredv2ds25.sced.jsonl is as follows: "problemdescription"
We release the raw data for our processed PythonEdu-Rs dataset, adopted from the original dataset from HuggingFaceTB team. The data format for each line in the 0368500filteredv2ds25.sced.jsonl is as follows: Some of the ios are empty. The reason is that when executing the code, the input/output sizes are too large and exceed our required constraints. Thus, they are not stored or used later. Note: Due to imperfect LLM-based transformations, some problem descriptions do not contain enough information to describe the code. We leave this as future work to further enhance our data and update it to a better version.
the raw data for our processed PythonEdu-Rs dataset, adopted from the original dataset from HuggingFaceTB team. The data format for each line in the 0368500filteredv2ds25.sced.jsonl is as follows: "problemdescription"
the raw data for our processed PythonEdu-Rs dataset, adopted from the original dataset from HuggingFaceTB team. The data format for each line in the 0368500filteredv2ds25.sced.jsonl is as follows: "problemdescription"
the raw data for our processed PythonEdu-Rs dataset, adopted from the original dataset from HuggingFaceTB team. The data format for each line in the 0368500filteredv2ds25.sced.jsonl is as follows: "problemdescription"
We release the raw data for our processed PythonEdu-Rs dataset, adopted from the original dataset from HuggingFaceTB team. The data format for each line in the 0368500filteredv2ds25.sced.jsonl is as follows: Some of the ios are empty. The reason is that when executing the code, the input/output sizes are too large and exceed our required constraints. Thus, they are not stored or used later. Note: Due to imperfect LLM-based transformations, some problem descriptions do not contain enough information to describe the code. We leave this as future work to further enhance our data and update it to a better version.
the raw data for our processed PythonEdu-Rs dataset, adopted from the original dataset from HuggingFaceTB team. The data format for each line in the 0368500filteredv2ds25.sced.jsonl is as follows: "problemdescription"
We release the raw data for our processed PythonEdu-Rs dataset, adopted from the original dataset from HuggingFaceTB team. The data format for each line in the 0368500filteredv2ds25.sced.jsonl is as follows: Some of the ios are empty. The reason is that when executing the code, the input/output sizes are too large and exceed our required constraints. Thus, they are not stored or used later. Note: Due to imperfect LLM-based transformations, some problem descriptions do not contain enough information to describe the code. We leave this as future work to further enhance our data and update it to a better version.
the raw data for our processed PythonEdu-Rs dataset, adopted from the original dataset from HuggingFaceTB team. The data format for each line in the 0368500filteredv2ds25.sced.jsonl is as follows: "problemdescription"
the raw data for our processed PythonEdu-Rs dataset, adopted from the original dataset from HuggingFaceTB team. The data format for each line in the 0368500filteredv2ds25.sced.jsonl is as follows: "problemdescription"
the raw data for our processed PythonEdu-Rs dataset, adopted from the original dataset from HuggingFaceTB team. The data format for each line in the 0368500filteredv2ds25.sced.jsonl is as follows: "problemdescription"
the raw data for our processed PythonEdu-Rs dataset, adopted from the original dataset from HuggingFaceTB team. The data format for each line in the 0368500filteredv2ds25.sced.jsonl is as follows: "problemdescription"
We release the raw data for our processed PythonEdu-Rs dataset, adopted from the original dataset from HuggingFaceTB team. The data format for each line in the 0368500filteredv2ds25.sced.jsonl is as follows: Some of the ios are empty. The reason is that when executing the code, the input/output sizes are too large and exceed our required constraints. Thus, they are not stored or used later. Note: Due to imperfect LLM-based transformations, some problem descriptions do not contain enough information to describe the code. We leave this as future work to further enhance our data and update it to a better version.
the raw data for our processed PythonEdu-Rs dataset, adopted from the original dataset from HuggingFaceTB team. The data format for each line in the 0368500filteredv2ds25.sced.jsonl is as follows: "problemdescription"
We release the raw data for our processed PythonEdu-Rs dataset, adopted from the original dataset from HuggingFaceTB team. The data format for each line in the 0368500filteredv2ds25.sced.jsonl is as follows: Some of the ios are empty. The reason is that when executing the code, the input/output sizes are too large and exceed our required constraints. Thus, they are not stored or used later. Note: Due to imperfect LLM-based transformations, some problem descriptions do not contain enough information to describe the code. We leave this as future work to further enhance our data and update it to a better version.
This dataset was created using LeRobot.
This is a filtered copy of the full ImageNet dataset consisting of the top 11821 (of 21841) classes by number of samples. It has been used to pretrain a number of in12k models in timm. The code and metadata for building this dataset from the original full ImageNet can be found at https://github.com/rwightman/imagenet-12k NOTE: This subset was filtered from the original fall11 ImageNet release which has been replaced by the winter21 release which removes close to 3000 synsets containing people, a number of these are of an offensive or sensitive nature. There is work in progress to filter a similar dataset from winter21, and there is already ImageNet-21k-P but with different thresholds &…
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