Bespoke Labs
  • Welcome
  • BESPOKE CURATOR
    • Getting Started
      • Quick Tour
      • Key Concepts
      • Visualize your dataset with the Bespoke Curator Viewer
      • Automatic recovery and caching
      • Structured Output
    • Save $$$ on LLM inference
      • Using OpenAI for batch inference
      • Using Anthropic for batch inference
      • Using Gemini for batch inference
      • Using Mistral for batch inference
      • Using kluster.ai for batch inference
    • How-to Guides
      • Using vLLM with Curator
      • Using Ollama with Curator
      • Using LiteLLM with curator
      • Handling Multimodal Data in Curator
      • Executing LLM-generated code
      • Using HuggingFace inference providers with Curator
    • Data Curation Recipes
      • Generating a diverse QA dataset
      • Using SimpleStrat block for generating diverse data
      • Curate Reasoning data with Claude-3.7 Sonnet
      • Synthetic Data for function calling
    • Finetuning Examples
      • Aspect based sentiment analysis
      • Finetuning a model to identify features of a product
    • API Reference
  • Models
    • Bespoke MiniCheck
      • Self-Hosting
      • Integrations
      • API Service
    • Bespoke MiniChart
    • OpenThinker
Powered by GitBook
On this page
  1. BESPOKE CURATOR
  2. Getting Started

Visualize your dataset with the Bespoke Curator Viewer

PreviousKey ConceptsNextAutomatic recovery and caching

Last updated 9 days ago

IMPORTANT: We recently are retiring our local curator-viewer , now switching to a hosted Bespoke Curator Viewer.

The hosted Bespoke Curator Viewer is a rich interface to visualize data, and makes visually inspecting the data much easier.

Example:

Before your Curator run, set the CURATOR_VIEWER environment variable.

Bash:

export CURATOR_VIEWER=1

Python/colab:

import os
os.environ["CURATOR_VIEWER"]="1"

With this enabled, as curator generates data, it gets uploaded and you can see the responses streaming in the viewer. The URL for the viewer is displayed right next to the rich progress.

Then, run on any Bespoke Curator scripts, here we use examples/poem-generation/poem.py as an example, and

The line 

Curator Viewer: ✨ Open Curator Viewer ✨

contains a clickable link (the following is an example viewer link, the link changes for each new Curator generation run) which opens the hosted Bespoke Curator Viewer in a new browser tab:

https://curator.bespokelabs.ai/datasets/845c7dd33b8b4242a24ff048b5f94354
Example Bespoke Curator Rich CLI logs on synthetic poems
Example Bespoke Curator Viewer on synthetic poem topics
link