size_categories:n<1K format:parquet modality:image modality:text library:datasets library:pandas library:mlcroissant library:polars library:distilabel region:us synthetic distilabel rlaif
---
size_categories: n<1K
dataset_info:
  features:
  - name: instruction
    dtype: string
  - name: image
    dtype: string
  - name: generation
    dtype: string
  - name: distilabel_metadata
    struct:
    - name: raw_input_vision_gen
      list:
      - name: content
        list:
        - name: image_url
          struct:
          - name: url
            dtype: string
        - name: text
          dtype: string
        - name: type
          dtype: string
      - name: role
        dtype: string
    - name: raw_output_vision_gen
      dtype: string
    - name: statistics_vision_gen
      struct:
      - name: input_tokens
        dtype: int64
      - name: output_tokens
        dtype: int64
  - name: model_name
    dtype: string
  splits:
  - name: train
    num_bytes: 1759
    num_examples: 1
  download_size: 18245
  dataset_size: 1759
configs:
- config_name: default
  data_files:
  - split: train
    path: data/train-*
tags:
- synthetic
- distilabel
- rlaif
---

<p align="left">
  <a href="https://github.com/argilla-io/distilabel">
    <img src="https://raw.githubusercontent.com/argilla-io/distilabel/main/docs/assets/distilabel-badge-light.png" alt="Built with Distilabel" width="200" height="32"/>
  </a>
</p>

# Dataset Card for test-vision-generation-Llama-3.2-11B-Vision-Instruct

This dataset has been created with [distilabel](https://distilabel.argilla.io/).



## Dataset Summary

This dataset contains a `pipeline.yaml` which can be used to reproduce the pipeline that generated it in distilabel using the `distilabel` CLI:

```console
distilabel pipeline run --config "https://huggingface.co/datasets/plaguss/test-vision-generation-Llama-3.2-11B-Vision-Instruct/raw/main/pipeline.yaml"
```

or explore the configuration:

```console
distilabel pipeline info --config "https://huggingface.co/datasets/plaguss/test-vision-generation-Llama-3.2-11B-Vision-Instruct/raw/main/pipeline.yaml"
```

## Dataset structure

The examples have the following structure per configuration:


<details><summary> Configuration: default </summary><hr>

```json
{
    "distilabel_metadata": {
        "raw_input_vision_gen": [
            {
                "content": [
                    {
                        "image_url": null,
                        "text": "What\u2019s in this image?",
                        "type": "text"
                    },
                    {
                        "image_url": {
                            "url": "https://upload.wikimedia.org/wikipedia/commons/thumb/d/dd/Gfp-wisconsin-madison-the-nature-boardwalk.jpg/2560px-Gfp-wisconsin-madison-the-nature-boardwalk.jpg"
                        },
                        "text": null,
                        "type": "image_url"
                    }
                ],
                "role": "user"
            }
        ],
        "raw_output_vision_gen": "This image depicts a wooden boardwalk weaving its way through a lush meadow, flanked by vibrant green grass that stretches towards the horizon under a calm and inviting sky.\n\nThe boardwalk runs straight ahead, away from the viewer, forming a clear pathway through the tall, lush green grass, crops or other plant types or an assortment of small trees and shrubs. This meadow is dotted with trees and shrubs, appearing to be healthy and green. The sky above is a beautiful blue with white clouds scattered throughout, adding a sense of tranquility to the scene.\n\nWhile this image appears to be of a natural landscape, because grass is",
        "statistics_vision_gen": {
            "input_tokens": 43,
            "output_tokens": 128
        }
    },
    "generation": "This image depicts a wooden boardwalk weaving its way through a lush meadow, flanked by vibrant green grass that stretches towards the horizon under a calm and inviting sky.\n\nThe boardwalk runs straight ahead, away from the viewer, forming a clear pathway through the tall, lush green grass, crops or other plant types or an assortment of small trees and shrubs. This meadow is dotted with trees and shrubs, appearing to be healthy and green. The sky above is a beautiful blue with white clouds scattered throughout, adding a sense of tranquility to the scene.\n\nWhile this image appears to be of a natural landscape, because grass is",
    "image": "https://upload.wikimedia.org/wikipedia/commons/thumb/d/dd/Gfp-wisconsin-madison-the-nature-boardwalk.jpg/2560px-Gfp-wisconsin-madison-the-nature-boardwalk.jpg",
    "instruction": "What\u2019s in this image?",
    "model_name": "meta-llama/Llama-3.2-11B-Vision-Instruct"
}
```

This subset can be loaded as:

```python
from datasets import load_dataset

ds = load_dataset("plaguss/test-vision-generation-Llama-3.2-11B-Vision-Instruct", "default")
```

Or simply as it follows, since there's only one configuration and is named `default`: 

```python
from datasets import load_dataset

ds = load_dataset("plaguss/test-vision-generation-Llama-3.2-11B-Vision-Instruct")
```


</details>




