Embeddoor - Embedding Visualization

File

Open CSV/Parquet... Load from Huggingface... Save as Parquet... Export as CSV...

Embedding

Create Embedding...

Dimensionality Reduction

Apply PCA... Apply t-SNE... Apply UMAP...

Selection

Store Selection... Restore Selection...

View

Add Panel... Toggle Toolbar Reset Layout

Plot Table Word Cloud Images Heatmap (Embedding) Heatmap (Columns) Pairwise Correlation Ridgeplot (Numeric Columns) IPython Terminal

Ready

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Create Embedding

Source Column: Provider: Model: Target Column Name:

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Apply PCA

Source Column (Embeddings): Number of Components: Target Column Base Name:

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Apply t-SNE

Source Column (Embeddings): Number of Components: Perplexity: Learning Rate: Max Iterations: Target Column Base Name:

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Apply UMAP

Source Column (Embeddings): Number of Components: Number of Neighbors: Min Distance: Metric: Target Column Base Name:

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Add New Panel

Panel Type:

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Load Dataset from Huggingface

Dataset Name: Split (optional):

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Store Selection

Selection Name:

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Restore Selection

Select Stored Selection: