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-0
    dtype: string
  - name: generation-0
    dtype: string
  - name: distilabel_metadata
    struct:
    - name: raw_output_chat_generation_0
      dtype: string
  splits:
  - name: train
    num_bytes: 1541989
    num_examples: 100
  download_size: 713581
  dataset_size: 1541989
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-v3

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-v3/raw/main/pipeline.yaml"
```

or explore the configuration:

```console
distilabel pipeline info --config "https://huggingface.co/datasets/distilabel-internal-testing/fine-preferences-magpie-v3/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 do you know about the interstellar medium?",
            "role": "user"
        },
        {
            "content": "The interstellar medium (ISM) is the material that fills the space between stars in a galaxy. It\u0027s a complex, dynamic environment that plays a crucial role in the formation and evolution of stars and galaxies. The ISM is composed of various phases of gas and dust, including neutral atomic hydrogen, molecular clouds, and ionized gas.\n\nOne of the fascinating aspects of the ISM is its ability to be shaped and influenced by powerful events, such as supernovae explosions and gamma-ray bursts (GRBs). These events can inject enormous amounts of energy into the ISM, creating large-scale structures like shells and holes that can span thousands of light-years.\n\nIn the case of GRBs, the explosion can heat the local gas to incredibly high temperatures, above 10 million degrees Kelvin, causing it to expand rapidly and create a massive bubble. This bubble can then \"snowplow\" through the surrounding ISM, pushing gas and dust out of the way and creating a large, hollow shell.\n\nThese shells can be quite massive, with energies reaching up to 10^53 ergs, which is an enormous amount of energy. Interestingly, some of these giant shells don\u0027t appear to have any obvious central star clusters, which has led some scientists to suggest that they might be the remnants of GRBs. However, it\u0027s also possible that the star clusters could be too old or too distant to be detected.\n\nWhat would you like to know more about? The formation of these shells, or perhaps the role of GRBs in shaping the ISM?",
            "role": "assistant"
        },
        {
            "content": "What exactly is a Gamma Ray Burst (GRB)?",
            "role": "user"
        },
        {
            "content": "Gamma-ray bursts (GRBs) are among the most powerful and enigmatic events in the universe. They are intense explosions of energy that release an enormous amount of radiation, primarily in the form of gamma rays, but also across the entire electromagnetic spectrum.\n\nGRBs are thought to occur when a massive star collapses or when two neutron stars or black holes merge. This collapse or merger releases an enormous amount of energy, which is then focused into a narrow beam of radiation that shoots out into space. This beam can travel millions of light-years, and if it happens to be pointed in our direction, we can detect it as a GRB.\n\nGRBs are incredibly powerful, releasing as much energy in a few seconds as the sun would produce over its entire 10-billion-year lifetime. They are also extremely brief, lasting anywhere from a few milliseconds to several minutes.\n\nOne of the most fascinating aspects of GRBs is their ability to affect the surrounding environment. As I mentioned earlier, they can heat the local gas to incredibly high temperatures, creating large-scale structures like shells and holes in the interstellar medium. They can also accelerate particles to incredible energies, producing powerful cosmic rays that can travel across vast distances.\n\nGRBs are also of great interest to astronomers because they can be used as cosmic probes, allowing us to study the distant universe in ways that would be impossible otherwise. By analyzing the radiation emitted by GRBs, scientists can learn about the composition of the interstellar medium, the properties of dark matter and dark energy, and even the expansion history of the universe itself.\n\nWould you like to know more about the different types of GRBs or their potential role in shaping the universe as we know it?",
            "role": "assistant"
        },
        {
            "content": "What is the role of the interstellar medium in the formation of stars?",
            "role": "user"
        }
    ],
    "distilabel_metadata": {
        "raw_output_chat_generation_0": " The interstellar medium (ISM) plays a critical role in the formation of stars. In fact, the process of star formation is tightly linked to the physical and chemical properties of the ISM.\n\nThe first step in star formation occurs within the dense, cold regions of the ISM known as molecular clouds. These clouds consist primarily of molecular hydrogen (H2) and other molecules, such as carbon monoxide (CO) and ammonia (NH3). They are also extremely cold, with temperatures ranging from about 10 to 50 degrees Kelvin.\n\nWithin these molecular"
    },
    "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",
    "generation-0": " The interstellar medium (ISM) plays a critical role in the formation of stars. In fact, the process of star formation is tightly linked to the physical and chemical properties of the ISM.\n\nThe first step in star formation occurs within the dense, cold regions of the ISM known as molecular clouds. These clouds consist primarily of molecular hydrogen (H2) and other molecules, such as carbon monoxide (CO) and ammonia (NH3). They are also extremely cold, with temperatures ranging from about 10 to 50 degrees Kelvin.\n\nWithin these molecular",
    "id": "\u003curn:uuid:e2300ad5-01dd-4e80-92b3-7ec88785cc9d\u003e",
    "int_score": 3,
    "language": "en",
    "language_score": 0.9126408100128174,
    "model_name-0": "mistralai/Mixtral-8x7B-Instruct-v0.1",
    "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-v3", "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-v3")
```


</details>
