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--- |
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license: apache-2.0 |
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size_categories: n<1K |
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dataset_info: |
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features: |
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- name: page_content |
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dtype: string |
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- name: parent_section |
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dtype: string |
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- name: url |
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dtype: string |
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- name: token_count |
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dtype: int64 |
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splits: |
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- name: train |
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num_bytes: 3445987.2 |
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num_examples: 1656 |
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- name: test |
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num_bytes: 861496.8 |
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num_examples: 414 |
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download_size: 1607895 |
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dataset_size: 4307484.0 |
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configs: |
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- config_name: default |
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data_files: |
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- split: train |
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path: data/train-* |
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- split: test |
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path: data/test-* |
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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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# Dataset Card for rag_qa_embedding_questions_0_60_0 |
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This dataset has been created with [distilabel](https://distilabel.argilla.io/). |
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## Dataset Summary |
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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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```console |
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distilabel pipeline run --config "https://huggingface.co/datasets/zenml/rag_qa_embedding_questions_0_60_0/raw/main/pipeline.yaml" |
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``` |
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or explore the configuration: |
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```console |
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distilabel pipeline info --config "https://huggingface.co/datasets/zenml/rag_qa_embedding_questions_0_60_0/raw/main/pipeline.yaml" |
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``` |
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## Dataset structure |
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The examples have the following structure per configuration: |
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<details><summary> Configuration: default </summary><hr> |
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```json |
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{ |
|
"anchor": "\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u251b\n\nExplore Service Connector TypesService Connector Types are not only templates used to instantiate Service Connectors, they also form a body of knowledge that documents best security practices and guides users through the complicated world of authentication and authorization.\n\nZenML ships with a handful of Service Connector Types that enable you right out-of-the-box to connect ZenML to cloud resources and services available from cloud providers such as AWS and GCP, as well as on-premise infrastructure. In addition to built-in Service Connector Types, ZenML can be easily extended with custom Service Connector implementations.\n\nTo discover the Connector Types available with your ZenML deployment, you can use the zenml service-connector list-types CLI command:\n\nzenml service-connector list-types\n\nExample Command Output\n\n\u250f\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u252f\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u252f\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u252f\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u252f\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u252f\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2513\n\n\u2503 NAME \u2502 TYPE \u2502 RESOURCE TYPES \u2502 AUTH METHODS \u2502 LOCAL \u2502 REMOTE \u2503\n\n\u2520\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u253c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u253c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u253c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u253c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u253c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2528\n\n\u2503 Kubernetes Service Connector \u2502 \ud83c\udf00 kubernetes \u2502 \ud83c\udf00 kubernetes-cluster \u2502 password \u2502 \u2705 \u2502 \u2705 \u2503\n\n\u2503 \u2502 \u2502 \u2502 token \u2502 \u2502 \u2503\n\n\u2520\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u253c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u253c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u253c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u253c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u253c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2528\n\n\u2503 Docker Service Connector \u2502 \ud83d\udc33 docker \u2502 \ud83d\udc33 docker-registry \u2502 password \u2502 \u2705 \u2502 \u2705 \u2503\n\n\u2520\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u253c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u253c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u253c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u253c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u253c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2528\n\n\u2503 Azure Service Connector \u2502 \ud83c\udde6 azure \u2502 \ud83c\udde6 azure-generic \u2502 implicit \u2502 \u2705 \u2502 \u2705 \u2503\n\n\u2503 \u2502 \u2502 \ud83d\udce6 blob-container \u2502 service-principal \u2502 \u2502 \u2503", |
|
"distilabel_metadata": { |
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"raw_output_generate_sentence_pair_0": "## Positive\n\nWhat command can be used to list available Service Connector Types in ZenML?\n\n## Negative\n\nCan you provide a list of popular Azure services?" |
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}, |
|
"model_name": "gpt-4o", |
|
"negative": "Can you provide a list of popular Azure services?", |
|
"parent_section": "how-to", |
|
"positive": "What command can be used to list available Service Connector Types in ZenML?", |
|
"token_count": 499, |
|
"url": "https://docs.zenml.io/v/docs/how-to/auth-management/service-connectors-guide" |
|
} |
|
``` |
|
|
|
This subset can be loaded as: |
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|
|
```python |
|
from datasets import load_dataset |
|
|
|
ds = load_dataset("zenml/rag_qa_embedding_questions_0_60_0", "default") |
|
``` |
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Or simply as it follows, since there's only one configuration and is named `default`: |
|
|
|
```python |
|
from datasets import load_dataset |
|
|
|
ds = load_dataset("zenml/rag_qa_embedding_questions_0_60_0") |
|
``` |
|
|
|
|
|
</details> |
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|
