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Review/erwan apr 18 #64

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Apr 19, 2024
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Original file line number Diff line number Diff line change
@@ -1,4 +1,4 @@
= Comparing Model Servers
= Comparing two LLMs
include::_attributes.adoc[]

So far, for this {ic-lab}, we have used the model https://huggingface.co/mistralai/Mistral-7B-Instruct-v0.2[Mistral-7B Instruct v2,window=_blank]. Although lighter than other models, it is still quite heavy and we need a large GPU to run it. Would we get as good results with a smaller model running on a CPU only? Let's try!
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16 changes: 10 additions & 6 deletions content/modules/ROOT/pages/05-05-process-claims.adoc
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Expand Up @@ -88,17 +88,19 @@ image::05/05-PVC-settings.png[PVC settings]

* Then press **Create**

== Run the pipeline
To run the pipeline, start by downloading the `process_claims.yaml` file locally. To do this, select the menu in the top left of the VSCode environment and navigate to *File -> Save As...*.
== Import the pipeline

[.bordershadow]
image::05/05-download-process-yaml.png[download process claims yaml]
To import the pipeline, start by downloading the `process_claims.yaml` file locally.
Navigate to `parasol-insurance/lab-materials/05/05-05` to find it.


Then go to your Data Science project and press Import Pipeline.
// * To do this, Select the menu in the top left of the VSCode environment and navigate to *File -> Save As...*.
// [.bordershadow]
// image::05/05-download-process-yaml.png[download process claims yaml]
// Then go to your Data Science project and press Import Pipeline.

* Start by downloading the `process_claims.yaml` file locally to your laptop
** In your VSCode Workbench, right click on the file, and select **Download**
** In your VSCode Workbench, right-click on the file, and select **Download**
** Save the file somewhere on your laptop
* Then go to the {rhoai} Dashboard
* Select your Data Science project
Expand All @@ -117,6 +119,8 @@ image::05/05-import-pipeline-highlighted.jpg[imported pipeline]

* Click **Import Pipeline** and you should see it appear under the pipelines section of your Project

== Run the pipeline

* Now go into the settings at the right side
* Click **Create Run** to create a new run of the pipeline you just added
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