> ## Documentation Index
> Fetch the complete documentation index at: https://docs.coreweave.com/llms.txt
> Use this file to discover all available pages before exploring further.

# Datasets Quick Start

> Create a reproducible dataset from task traffic and inspect its training and validation rows.

<Note>
  Before you begin, send representative traffic through a task or identify an existing W\&B project containing compatible Weave calls.
</Note>

<Steps>
  <Step title="Open the task">
    Select the task you want to improve, open **Datasets**, and choose **Create dataset**.
  </Step>

  <Step title="Choose the source">
    Use **Task traffic** for calls captured by the Model Distillation proxy. Select **Existing W\&B project** only for compatible calls logged outside the task.
  </Step>

  <Step title="Define a fixed snapshot">
    Choose **After** and **Before** dates, the task version, and the provider/model that produced the behavior you want to learn. Set a maximum only when you want to sample a larger result set.
  </Step>

  <Step title="Reserve validation data">
    Start with 20% validation data. Model Distillation keeps related scenarios, traces, and conversations in the same split so the evaluation does not see near-duplicates from training.
  </Step>

  <Step title="Create and inspect">
    Start the build and wait for **Ready**. Review several train and validation rows, check message and output fidelity, and delete clearly unusable entries before training.
  </Step>
</Steps>

The dataset is now ready for [relabeling](/model-distillation/studio/relabeling), [fine-tuning](/model-distillation/studio/fine-tuning-quickstart), and [evaluations](/model-distillation/studio/evaluations-quickstart).

<Accordion title="API: Create a dataset (POST /tasks/{alias}/datasets)">
  Use fixed timestamps so rerunning your workflow describes the same source window:

  ```bash theme={"system"}
  curl --request POST \
    --url "https://distillation.training.wandb.ai/v1/tasks/ticket-classifier/datasets" \
    --header "Authorization: Bearer $WANDB_API_KEY" \
    --header "Wandb-Entity: your-team" \
    --header "Content-Type: application/json" \
    --data '{
      "name": "recent-production",
      "params": {
        "query": {
          "source": "task",
          "after": "2026-08-01T00:00:00.000Z",
          "before": "2026-09-01T00:00:00.000Z",
          "filters": {"task_version": 1}
        },
        "sampling": {"strategy": "random", "limit": 20000},
        "split": {"val": 0.2, "by": "trace"}
      }
    }'
  ```

  The response contains the dataset ID. Poll its returned resource until `status` is `ready`; see [Create a dataset](/model-distillation/reference/management).
</Accordion>