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--- |
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dataset_info: |
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features: |
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- name: instruction |
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dtype: string |
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- name: context |
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dtype: string |
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- name: response |
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dtype: string |
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- name: category |
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dtype: string |
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splits: |
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- name: train |
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num_bytes: 3243541 |
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num_examples: 4000 |
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download_size: 2050955 |
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dataset_size: 3243541 |
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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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license: apache-2.0 |
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task_categories: |
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- table-question-answering |
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- question-answering |
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- text-generation |
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language: |
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- en |
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size_categories: |
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- 1K<n<10K |
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--- |
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# Databricks-Dolly-8k |
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The resulting dataset contains **8000 samples** of the [databricks/databricks-dolly-15k](https://huggingface.co/datasets/databricks/databricks-dolly-15k) dataset. |
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This split of an even smaller subset is provided for very fast experimentation and evaluation of models when computational resources are highly limited or for quick prototyping. |
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## Dataset Structure |
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The dataset is provided as a `DatasetDict` with the following splits: |
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* **`train`**: Contains 8000 samples. |
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Each split contains the following features, identical to the original dataset: |
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* `id`: The unique identifier for each sample. |
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* `instruction`: The instruction or prompt for the task. |
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* `response`: The response to the given instruction. |
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* `context`: Additional context or information related to the instruction. |
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* `source`: The source of the sample. |
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## Usage |
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You can easily load this split dataset using the `datasets` library: |
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```python |
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from datasets import load_dataset |
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databricks_dolly_8k = load_dataset("Vishva007/Databricks-Dolly-8k") |
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print(databricks_dolly_8k) |
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print(databricks_dolly_8k["train"][0]) |
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``` |
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## Example Usage |
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Here’s an example of how you might use this dataset in a Python script: |
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```python |
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from datasets import load_dataset |
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# Load the dataset |
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databricks_dolly_8k = load_dataset("Vishva007/Databricks-Dolly-8k") |
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# Print the first sample in the training set |
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print(databricks_dolly_8k["train"][0]) |
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# Access specific fields from the first sample |
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sample = databricks_dolly_8k["train"][0] |
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print(f"ID: {sample['id']}") |
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print(f"Instruction: {sample['instruction']}") |
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print(f"Response: {sample['response']}") |
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print(f"Context: {sample['context']}") |
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print(f"Source: {sample['source']}") |
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``` |
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## Dataset Info |
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### Features |
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- `id`: The unique identifier for each sample. |
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- `instruction`: The instruction or prompt for the task. |
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- `response`: The response to the given instruction. |
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- `context`: Additional context or information related to the instruction. |
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- `source`: The source of the sample. |
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### Splits |
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- **`train`**: Contains 8000 samples. |
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## License |
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This dataset is derived from the [databricks/databricks-dolly-15k](https://huggingface.co/datasets/databricks/databricks-dolly-15k) dataset, which is licensed under the [Apache License 2.0](https://www.apache.org/licenses/LICENSE-2.0). |
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For more details about the original dataset, please refer to the [official documentation](https://huggingface.co/datasets/databricks/databricks-dolly-15k). |
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--- |
