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Update README.md

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  1. README.md +3 -2
README.md CHANGED
@@ -94,7 +94,7 @@ Start exploring with a simple view that leverages embeddings to identify relevan
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  from renumics import spotlight
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  df = dataset.to_pandas()
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- spotlight.show(df, dtype={'audio': spotlight.Audio, "ast-finetuned-audioset-10-10-0.4593-embeddings": spotlight.Embedding}, layout=ds_builder.config.get_layout(config="standard"))
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  ```
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  You can use the UI to interactively configure the view on the data. Depending on the concrete taks (e.g. model comparison, debugging, outlier detection) you might want to leverage different enrichments and metadata.
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@@ -105,7 +105,8 @@ This example shows a view that is suitable to compare the results of two differe
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  from renumics import spotlight
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  df = dataset.to_pandas()
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- spotlight.show(df, dtype={'audio': spotlight.Audio, "ast-finetuned-audioset-10-10-0.4593-embeddings": spotlight.Embedding}, layout=ds_builder.config.get_layout(config="standard"))
 
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  ```
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  ## Using custom model results and enrichments
 
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  from renumics import spotlight
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  df = dataset.to_pandas()
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+ spotlight.show(df, dtype={'path': spotlight.Audio, "embeddings_ast-finetuned-audioset-10-10-0.4593": spotlight.Embedding})
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  ```
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  You can use the UI to interactively configure the view on the data. Depending on the concrete taks (e.g. model comparison, debugging, outlier detection) you might want to leverage different enrichments and metadata.
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  from renumics import spotlight
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  df = dataset.to_pandas()
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+ # spotlight.show(df, dtype={'audio': spotlight.Audio, "ast-finetuned-audioset-10-10-0.4593-embeddings": spotlight.Embedding}, layout=ds_builder.config.get_layout(config="standard"))
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+ # todo
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  ```
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  ## Using custom model results and enrichments