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| "text": "Hub documentation Using Datasets Hub View all docs AWS Trainium & Inferentia Accelerate Amazon SageMaker Argilla AutoTrain Bitsandbytes Chat UI Dataset viewer Datasets Diffusers Distilabel Evaluate Gradio Hub Hub Python Library Huggingface.js Inference Endpoints (dedicated) Inference Providers LeRobot Leaderboards Lighteval Optimum PEFT Safetensors Sentence Transformers TRL Tasks Text Embeddings Inference Text Generation Inference Tokenizers Transformers Transformers.js smolagents timm Search documentation EN Join the Hugging Face community and get access to the augmented documentation experience Collaborate on models, datasets and Spaces Faster examples with accelerated inference Switch between documentation themes Sign Up to get started Using Datasets Once youve found an interesting dataset on the Hugging Face Hub, you can load the dataset using Datasets. You can click on the Use this dataset button to copy the code to load a dataset. First you need to Login with your Hugging Face account , for example using: Copied huggingface- cli login And then you can load a dataset from the Hugging Face Hub using Copied from datasets import load_dataset dataset = load_dataset( \"username/my_dataset\" ) # or load the separate splits if the dataset has train/validation/test splits train_dataset = load_dataset( \"username/my_dataset\" , split= \"train\" ) valid_dataset = load_dataset( \"username/my_dataset\" , split= \"validation\" ) test_dataset = load_dataset( \"username/my_dataset\" , split= \"test\" ) You can also upload datasets to the Hugging Face Hub: Copied my_new_dataset.push_to_hub( \"username/my_new_dataset\" ) This creates a dataset repository username/my_new_dataset containing your Dataset in Parquet format, that you can reload later. For more information about using Datasets, check out the tutorials and how-to guides available in the Datasets documentation. < > Update on GitHub Dask Distilabel", | |
| "title": "Using 🤗 Datasets", | |
| "url": "https://huggingface.co/docs/hub/datasets-usage", | |
| "word_count": 264, | |
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| } | |
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