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  ---
 
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  dataset_info:
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  features:
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  - name: prompt
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  data_files:
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  - split: train
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  path: data/train-*
 
 
 
 
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  ---
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  ---
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+ size_categories: n<1K
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  dataset_info:
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  features:
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  - name: prompt
 
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  data_files:
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  - split: train
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  path: data/train-*
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+ tags:
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+ - synthetic
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+ - distilabel
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+ - rlaif
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  ---
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+
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+ <p align="left">
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+ <a href="https://github.com/argilla-io/distilabel">
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+ <img src="https://raw.githubusercontent.com/argilla-io/distilabel/main/docs/assets/distilabel-badge-light.png" alt="Built with Distilabel" width="200" height="32"/>
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+ </a>
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+ </p>
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+
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+ # Dataset Card for img-prefs-distilabel-artifacts-sample
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+
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+ This dataset has been created with [distilabel](https://distilabel.argilla.io/).
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+
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+
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+
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+ ## Dataset Summary
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+
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+ This dataset contains a `pipeline.yaml` which can be used to reproduce the pipeline that generated it in distilabel using the `distilabel` CLI:
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+
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+ ```console
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+ distilabel pipeline run --config "https://huggingface.co/datasets/dvilasuero/img-prefs-distilabel-artifacts-sample/raw/main/pipeline.yaml"
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+ ```
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+
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+ or explore the configuration:
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+
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+ ```console
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+ distilabel pipeline info --config "https://huggingface.co/datasets/dvilasuero/img-prefs-distilabel-artifacts-sample/raw/main/pipeline.yaml"
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+ ```
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+
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+ ## Dataset structure
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+
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+ The examples have the following structure per configuration:
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+
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+
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+ <details><summary> Configuration: default </summary><hr>
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+
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+ ```json
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+ {
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+ "images": [
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+ {
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+ "path": "artifacts/flux/images/90b884933d23c4d57ca01dbe2898d405.jpeg"
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+ },
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+ {
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+ "path": "artifacts/sdxl/images/90b884933d23c4d57ca01dbe2898d405.jpeg"
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+ },
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+ {
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+ "path": "artifacts/flux_task_2/images/90b884933d23c4d57ca01dbe2898d405.jpeg"
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+ }
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+ ],
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+ "models": [
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+ "black-forest-labs/FLUX.1-schnell",
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+ "stabilityai/stable-diffusion-xl-base-1.0",
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+ "black-forest-labs/FLUX.1-schnell"
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+ ],
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+ "prompt": "intelligence"
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+ }
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+ ```
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+
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+ This subset can be loaded as:
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+
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+ ```python
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+ from datasets import load_dataset
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+
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+ ds = load_dataset("dvilasuero/img-prefs-distilabel-artifacts-sample", "default")
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+ ```
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+
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+ Or simply as it follows, since there's only one configuration and is named `default`:
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+
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+ ```python
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+ from datasets import load_dataset
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+
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+ ds = load_dataset("dvilasuero/img-prefs-distilabel-artifacts-sample")
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+ ```
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+
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+
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+ </details>
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+
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+
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+
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+ ## Artifacts
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+
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+
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+ * **Step**: `flux`
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+
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+ * **Artifact name**: `images`
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+
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+ * `type`: image
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+
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+ * `library`: diffusers
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+
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+
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+
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+ * **Step**: `sdxl`
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+
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+ * **Artifact name**: `images`
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+
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+ * `type`: image
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+
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+ * `library`: diffusers
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+
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+
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+
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+ * **Step**: `flux_task_2`
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+
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+ * **Artifact name**: `images`
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+
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+ * `type`: image
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+
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+ * `library`: diffusers
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+
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+