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trying this again
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pat-alt committed Jul 5, 2023
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4 changes: 2 additions & 2 deletions _freeze/docs/src/how_to_guides/llm/execute-results/md.json

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2,318 changes: 1,159 additions & 1,159 deletions _freeze/docs/src/tutorials/classification/figure-commonmark/cell-10-output-1.svg
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2 changes: 1 addition & 1 deletion docs/src/how_to_guides/llm.md
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Expand Up @@ -207,7 +207,7 @@ prediction_set(mach, refined_query)[2]

Below we include a short demo video that shows the REPL-based chatbot in action.

![](../../../docs/src/www/demo_llm.gif)
![](../www/demo_llm.gif)

## Final Remarks

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2 changes: 1 addition & 1 deletion docs/src/how_to_guides/llm.qmd
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Expand Up @@ -188,7 +188,7 @@ prediction_set(mach, refined_query)[2]

Below we include a short demo video that shows the REPL-based chatbot in action.

![](/docs/src/www/demo_llm.gif)
![](../www/demo_llm.gif)

## Final Remarks

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4 changes: 0 additions & 4 deletions docs/src/tutorials/classification.md

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2 changes: 1 addition & 1 deletion docs/src/tutorials/classification.qmd
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Expand Up @@ -164,7 +164,7 @@ Well, for low coverage rates (roughly ``<0.9``) the conformal prediction set doe
These two examples illustrate an interesting point: for regions characterized by high predictive uncertainty, conformal prediction sets are typically empty (for low coverage) or large (for high coverage). While set-valued predictions may be something to get used to, this notion is overall intuitive.
```{julia}
#| output: true
#| output: false
#| label: fig-anim
#| fig-cap: "The effect of the coverage rate on the conformal prediction set. Softmax probabilities are shown on the left. The size of the prediction set is shown on the right."
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2,318 changes: 1,159 additions & 1,159 deletions docs/src/tutorials/classification_files/figure-commonmark/cell-10-output-1.svg
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