Update README.md

README.md

@@ -8,11 +8,85 @@ dataset_info:
     dtype: image
   splits:
   - name: train
-    num_bytes: 282285477.0
+    num_bytes: 282285477
     num_examples: 10000
   - name: test
     num_bytes: 56612023.875
     num_examples: 2001
   download_size: 320681179
   dataset_size: 338897500.875
+task_categories:
+- text-to-image
+multilinguality:
+- monolingual
+language:
+- de
+size_categories:
+- 1K<n<10K
+source_datasets:
+- original
+pretty_name: Fashion12k DE
 ---
+# Dataset Card for Fashion12K DE
+
+## Dataset Description
+
+- **Repository:** [Fashion12K](https://github.com/Toloka/Fashion12K_german_queries)
+- 
+### Dataset Summary
+
+This dataset is a German-language dataset based on the [Fashion12K](https://github.com/Toloka/Fashion12K_german_queries) dataset, which originally contains both English and German text descriptions for each item.
+
+## Dataset Structure
+
+### Data Instances
+
+Each data point consists of a 'text' and an 'image' field, where the 'text' field describes an item of clothing in German, and the 'image' field contains and image of that item of clothing.
+
+### Data Fields
+
+- 'text': A string describing the item of clothing.
+- 'image': A `PIL.Image.Image` object containing the image. Note that when accessing the image column: dataset[0]["image"] the image file is automatically decoded. Decoding of a large number of image files might take a significant amount of time. Thus it is important to first query the sample index before the "image" column, i.e. dataset[0]["image"] should always be preferred over dataset["image"][0].
+
+### Data Splits
+
+|            | train | test |
+|------------|-------|------|
+| # of items | 10000 | 2001 |
+| test       |       |      |
+
+## Dataset Creation
+
+### Curation Rationale
+
+Fashion12K DE was created for the purposes of training multilingual CLIP models
+
+### Source Data
+
+#### Initial Data Collection and Normalization
+
+Images were sampled from the [Fashion200K dataset](https://github.com/xthan/fashion-200k)
+
+### Annotations
+
+#### Annotation process
+
+Data was annotated using [Toloka](https://toloka.ai/). See their site for more details
+
+## Additional Information
+
+### Dataset Curators
+
+[More Information Needed]
+
+### Licensing Information
+
+[More Information Needed]
+
+### Citation Information
+
+[More Information Needed]
+
+### Contributions
+
+[More Information Needed]