Create README.md

README.md

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+# Dataset Card for STL-10
+
+<!-- Provide a quick summary of the dataset. -->
+
+## Dataset Details
+
+### Dataset Description
+
+<!-- Provide a longer summary of what this dataset is. -->
+The STL-10 dataset is an image recognition dataset for developing unsupervised feature learning, deep learning, self-taught learning algorithms. It is inspired by the CIFAR-10 dataset but with some modifications. In particular, each class has fewer labeled training examples than in CIFAR-10, but a very large set of unlabeled examples is provided to learn image models prior to supervised training. 
+
+### Dataset Sources
+
+<!-- Provide the basic links for the dataset. -->
+
+- **Homepage:** https://cs.stanford.edu/~acoates/stl10/
+- **Paper:** Coates, A., Ng, A., & Lee, H. (2011, June). An analysis of single-layer networks in unsupervised feature learning. In Proceedings of the fourteenth international conference on artificial intelligence and statistics (pp. 215-223). JMLR Workshop and Conference Proceedings.
+
+## Dataset Structure
+
+<!-- This section provides a description of the dataset fields, and additional information about the dataset structure such as criteria used to create the splits, relationships between data points, etc. -->
+
+#### Labeled
+Total images: 13,000
+
+Classes: 10 categories (airplane, bird, car, cat, deer, dog, horse, monkey, ship, truck)
+
+Splits:
+
+- **Train:** 5,000 images
+
+- **Test:** 8,000 images
+
+Image specs: 96x96 pixels, RGB
+
+#### Unlabeled
+Total images: 100,000
+
+Classes: all labels are -1
+
+## Example Usage
+Below is a quick example of how to load this dataset via the Hugging Face Datasets library.
+```
+from datasets import load_dataset  
+
+# Load the dataset  
+dataset = load_dataset("randall-lab/stl10", split="train", trust_remote_code=True)  
+# dataset = load_dataset("randall-lab/stl10", split="test", trust_remote_code=True)
+# dataset = load_dataset("randall-lab/stl10", split="unlabeled", trust_remote_code=True)  
+
+# Access a sample from the dataset  
+example = dataset[0]  
+image = example["image"]  
+label = example["label"]  
+
+image.show()  # Display the image  
+print(f"Label: {label}")
+```
+
+## Citation
+
+<!-- If there is a paper or blog post introducing the dataset, the APA and Bibtex information for that should go in this section. -->
+
+**BibTeX:**
+
+@inproceedings{coates2011analysis,
+  title={An analysis of single-layer networks in unsupervised feature learning},
+  author={Coates, Adam and Ng, Andrew and Lee, Honglak},
+  booktitle={Proceedings of the fourteenth international conference on artificial intelligence and statistics},
+  pages={215--223},
+  year={2011},
+  organization={JMLR Workshop and Conference Proceedings}
+}