size_categories:n<1K format:parquet modality:tabular 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: text
    dtype: string
  - name: id
    dtype: string
  - name: dump
    dtype: string
  - name: url
    dtype: string
  - name: file_path
    dtype: string
  - name: language
    dtype: string
  - name: language_score
    dtype: float64
  - name: token_count
    dtype: int64
  - name: score
    dtype: float64
  - name: int_score
    dtype: int64
  - name: system_prompt
    dtype: string
  - name: conversation
    list:
    - name: content
      dtype: string
    - name: role
      dtype: string
  - name: model_name
    dtype: string
  splits:
  - name: train
    num_bytes: 1559824
    num_examples: 100
  download_size: 707746
  dataset_size: 1559824
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 fine-preferences-magpie-v1

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/distilabel-internal-testing/fine-preferences-magpie-v1/raw/main/pipeline.yaml"
```

or explore the configuration:

```console
distilabel pipeline info --config "https://huggingface.co/datasets/distilabel-internal-testing/fine-preferences-magpie-v1/raw/main/pipeline.yaml"
```

## Dataset structure

The examples have the following structure per configuration:


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

```json
{
    "conversation": [
        {
            "content": "You\u0027re a helpful AI assistant that responds user questions based on a document\u0027s content, without explicitly mentioning the document. Follow these guidelines:\n\n## 1. Preparation\n- Absorb the document\u0027s main topics, key points, and themes.\n- The conversation will be between two participants: a curious user and a knowledgeable AI assistant.\n\n## 2. Conversation Structure\n- Start with a user query related to the document\u0027s main topic, without referencing the document.\n- The AI assistant should respond using information from the document, presented as its own knowledge.\n- Alternate between user questions/comments and AI responses.\n- Cover main points from the document through this natural dialogue.\n\n## 3. User Characteristics\n- The user should ask relevant questions and express interest in the topic.\n- User messages can include follow-up questions, requests for clarification, or sharing of personal opinions.\n- The user\u0027s knowledge level can vary, allowing the AI to explain concepts when necessary.\n\n## 4. AI Assistant Characteristics\n- Respond comprehensively and accurately based on the document\u0027s content.\n- Adapt explanations to the user\u0027s apparent level of understanding.\n- Offer analogies, examples, or scenarios to illustrate points when appropriate.\n- Be prepared to clarify or expand on previous statements if the user asks.\n\n## 5. Engagement\n- Maintain a helpful and engaging tone throughout the conversation.\n- The AI should encourage deeper exploration of topics through its responses.\n- Conclude the conversation with a summary or thought-provoking insight.\n\n## 6. General Guidelines\n- Ensure the conversation flows naturally and coherently.\n- The AI\u0027s knowledge should seem broad but not omniscient, reflecting the document\u0027s scope.\n- Adapt to any specific instructions provided about the conversation\u0027s focus or detail level.\n\n## 7. User Role Refinement\n- The user should primarily ask follow-up questions based on the AI\u0027s previous response.\n- User questions should build on the information just provided, showing curiosity and engagement with the topic at hand.\n- Avoid having the user abruptly introduce new topics from the document without context.\n\nRemember: Never mention or directly reference the source document in the generated conversation. The AI assistant should present information as if it\u0027s part of its general knowledge base.\n\n## Document\n\nPrevious abstract Next abstract\nSession 40 - The Interstellar Medium.\nDisplay session, Tuesday, June 09\nGamma Ray Burst (GRB) explosions can make kpc-size shells and holes in the interstellar media (ISM) of spiral galaxies if much of the energy heats the local gas to above 10^7 K. Disk blowout is probably the major cause for energy loss in this case, but the momentum acquired during the pressurized expansion phase can be large enough that the bubble still snowplows to a kpc diameter. This differs from the standard model for the origin of such shells by multiple supernovae, which may have problems with radiative cooling, evaporative losses, and disk blow-out. Evidence for giant shells with energies of \\sim10^53 ergs are summarized. Some contain no obvious central star clusters and may be GRB remnants, although sufficiently old clusters would be hard to detect. The expected frequency of GRBs in normal galaxies can account for the number of such shells.\nProgram listing for Tuesday\n",
            "role": "system"
        },
        {
            "content": "What is the interstellar medium?",
            "role": "user"
        },
        {
            "content": "The interstellar medium, or ISM, refers to the material that fills the space between stars within a galaxy. It\u0027s made up of various gases, including hydrogen, helium, and heavier elements, as well as dust particles. The ISM plays a crucial role in the formation of new stars and planets, as it provides the raw material for these processes.\n\nThink of the ISM as a vast, diffuse network of gas and dust that permeates the galaxy. It\u0027s not a uniform entity, though \u2013 the ISM can be found in different phases, ranging from cold, dense molecular clouds to hot, ionized plasma. The temperature and density of the ISM can vary greatly, depending on factors like the proximity to stars, supernovae, or other energetic events.\n\nIn the context of galaxies like our own Milky Way, the ISM is an essential component that helps shape the galaxy\u0027s structure and evolution. It\u0027s a dynamic, constantly interacting system that influences the formation of stars, the growth of supermassive black holes, and even the distribution of heavy elements throughout the galaxy.\n\nWould you like to know more about how the ISM is affected by energetic events, like supernovae or gamma-ray bursts?",
            "role": "assistant"
        },
        {
            "content": "What are gamma-ray bursts?",
            "role": "user"
        },
        {
            "content": "Gamma-ray bursts, or GRBs, are incredibly powerful and explosive events that occur in the universe. They are the most luminous electromagnetic events known, releasing enormous amounts of energy in the form of gamma rays, X-rays, and other types of electromagnetic radiation.\n\nGRBs are thought to occur when massive stars collapse or when neutron stars or black holes merge. These events release an enormous amount of energy, which is focused into a narrow beam of radiation that can travel across vast distances through space.\n\nImagine a colossal explosion that releases as much energy as a billion suns, but concentrated into a beam that\u0027s only a few degrees wide. That\u0027s roughly the scale of a gamma-ray burst! This energy output is so immense that it can be detected from millions of light-years away, making GRBs visible from distant corners of the universe.\n\nGRBs are often associated with supernovae, which are massive star explosions. However, GRBs are much more powerful and can occur in galaxies that are otherwise quiet and inactive. They can also create massive shockwaves that can affect the surrounding interstellar medium, as we discussed earlier.\n\nThe effects of GRBs on their host galaxies can be significant. They can create massive bubbles and holes in the interstellar medium, which can then affect the formation of new stars and planets. In some cases, GRBs might even be responsible for creating the giant shells and holes we see in some galaxies.\n\nWould you like to know more about how GRBs interact with the interstellar medium and shape the evolution of galaxies?",
            "role": "assistant"
        },
        {
            "content": "What kind of shells and holes are we talking about?",
            "role": "user"
        },
        {
            "content": "When I mentioned shells and holes, I was referring to large-scale structures that can be found in the interstellar medium of galaxies. These shells and holes are essentially cavities or bubbles in the ISM, which can be hundreds or even thousands of light-years across.\n\nImagine a giant bubble expanding through the ISM, pushing aside the surrounding gas and dust. As it grows, it can create a shell of denser material around its perimeter, with a hollow interior. These shells can be so large that they can encompass entire star-forming regions or even affect the overall structure of the galaxy.\n\nIn the context of GRBs, these shells and holes are thought to be created when the burst\u0027s energy output heats up and expels the surrounding ISM, creating a massive bubble that can expand to enormous sizes. The momentum imparted to the ISM during this process can be so great that it can even \"snowplow\" through the surrounding material, creating a large cavity or hole.\n\nThese shells and holes can be important features of a galaxy\u0027s structure, as they can affect the flow of gas and dust, influence the formation of new stars, and even impact the galaxy\u0027s overall evolution. In some cases, these structures can be so large and prominent that they can be seen in distant galaxies, providing astronomers with valuable clues about the history and evolution of those galaxies.\n\nWould you like to know more about how these shells and holes might be related to GRBs, or how they can be used to study galaxy evolution?",
            "role": "assistant"
        }
    ],
    "dump": "CC-MAIN-2013-20",
    "file_path": "s3://commoncrawl/crawl-data/CC-MAIN-2013-20/segments/1368696381249/warc/CC-MAIN-20130516092621-00000-ip-10-60-113-184.ec2.internal.warc.gz",
    "id": "\u003curn:uuid:e2300ad5-01dd-4e80-92b3-7ec88785cc9d\u003e",
    "int_score": 3,
    "language": "en",
    "language_score": 0.9126408100128174,
    "model_name": "meta-llama/Meta-Llama-3-70B-Instruct",
    "score": 2.765625,
    "system_prompt": "You\u0027re a helpful AI assistant that responds user questions based on a document\u0027s content, without explicitly mentioning the document. Follow these guidelines:\n\n## 1. Preparation\n- Absorb the document\u0027s main topics, key points, and themes.\n- The conversation will be between two participants: a curious user and a knowledgeable AI assistant.\n\n## 2. Conversation Structure\n- Start with a user query related to the document\u0027s main topic, without referencing the document.\n- The AI assistant should respond using information from the document, presented as its own knowledge.\n- Alternate between user questions/comments and AI responses.\n- Cover main points from the document through this natural dialogue.\n\n## 3. User Characteristics\n- The user should ask relevant questions and express interest in the topic.\n- User messages can include follow-up questions, requests for clarification, or sharing of personal opinions.\n- The user\u0027s knowledge level can vary, allowing the AI to explain concepts when necessary.\n\n## 4. AI Assistant Characteristics\n- Respond comprehensively and accurately based on the document\u0027s content.\n- Adapt explanations to the user\u0027s apparent level of understanding.\n- Offer analogies, examples, or scenarios to illustrate points when appropriate.\n- Be prepared to clarify or expand on previous statements if the user asks.\n\n## 5. Engagement\n- Maintain a helpful and engaging tone throughout the conversation.\n- The AI should encourage deeper exploration of topics through its responses.\n- Conclude the conversation with a summary or thought-provoking insight.\n\n## 6. General Guidelines\n- Ensure the conversation flows naturally and coherently.\n- The AI\u0027s knowledge should seem broad but not omniscient, reflecting the document\u0027s scope.\n- Adapt to any specific instructions provided about the conversation\u0027s focus or detail level.\n\n## 7. User Role Refinement\n- The user should primarily ask follow-up questions based on the AI\u0027s previous response.\n- User questions should build on the information just provided, showing curiosity and engagement with the topic at hand.\n- Avoid having the user abruptly introduce new topics from the document without context.\n\nRemember: Never mention or directly reference the source document in the generated conversation. The AI assistant should present information as if it\u0027s part of its general knowledge base.\n\n## Document\n\nPrevious abstract Next abstract\nSession 40 - The Interstellar Medium.\nDisplay session, Tuesday, June 09\nGamma Ray Burst (GRB) explosions can make kpc-size shells and holes in the interstellar media (ISM) of spiral galaxies if much of the energy heats the local gas to above 10^7 K. Disk blowout is probably the major cause for energy loss in this case, but the momentum acquired during the pressurized expansion phase can be large enough that the bubble still snowplows to a kpc diameter. This differs from the standard model for the origin of such shells by multiple supernovae, which may have problems with radiative cooling, evaporative losses, and disk blow-out. Evidence for giant shells with energies of \\sim10^53 ergs are summarized. Some contain no obvious central star clusters and may be GRB remnants, although sufficiently old clusters would be hard to detect. The expected frequency of GRBs in normal galaxies can account for the number of such shells.\nProgram listing for Tuesday\n",
    "text": "Previous abstract Next abstract\nSession 40 - The Interstellar Medium.\nDisplay session, Tuesday, June 09\nGamma Ray Burst (GRB) explosions can make kpc-size shells and holes in the interstellar media (ISM) of spiral galaxies if much of the energy heats the local gas to above 10^7 K. Disk blowout is probably the major cause for energy loss in this case, but the momentum acquired during the pressurized expansion phase can be large enough that the bubble still snowplows to a kpc diameter. This differs from the standard model for the origin of such shells by multiple supernovae, which may have problems with radiative cooling, evaporative losses, and disk blow-out. Evidence for giant shells with energies of \\sim10^53 ergs are summarized. Some contain no obvious central star clusters and may be GRB remnants, although sufficiently old clusters would be hard to detect. The expected frequency of GRBs in normal galaxies can account for the number of such shells.\nProgram listing for Tuesday",
    "token_count": 208,
    "url": "http://aas.org/archives/BAAS/v30n2/aas192/abs/S040015.html"
}
```

This subset can be loaded as:

```python
from datasets import load_dataset

ds = load_dataset("distilabel-internal-testing/fine-preferences-magpie-v1", "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("distilabel-internal-testing/fine-preferences-magpie-v1")
```


</details>
