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v2.0.0b4
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andreybavt committed Jun 7, 2023
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2 changes: 1 addition & 1 deletion README.md
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Expand Up @@ -84,7 +84,7 @@ And of course, Giskard works with any model, any environment and integrates seam

### Installation
```sh
pip install 'giskard[server]==2.0.0b3'
pip install 'giskard[server]==2.0.0b4'

giskard server start
```
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2 changes: 1 addition & 1 deletion gradle.properties
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@@ -1,4 +1,4 @@
giskardVersion=2.0.0b3
giskardVersion=2.0.0b4

rootProject.name=giskard
profile=dev
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2 changes: 1 addition & 1 deletion python-client/README.md
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Expand Up @@ -89,7 +89,7 @@ And of course, Giskard works with any model, any environment and integrates seam

### Installation
```sh
pip install "giskard[server]==2.0.0b3"
pip install "giskard[server]==2.0.0b4"

giskard server start
```
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Expand Up @@ -40,7 +40,7 @@
},
"outputs": [],
"source": [
"!pip install \"giskard==2.0.0b3\""
"!pip install \"giskard==2.0.0b4\""
]
},
{
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Expand Up @@ -2425,7 +2425,7 @@
"\n",
"# To start the Giskard server, run in your terminal within the Python\n",
"# environment containing the dependencies of your model: \n",
"giskard server start --version 2.0.0b3\n",
"giskard server start --version 2.0.0b4\n",
"giskard worker start -u http://localhost:19000/\n",
"\n",
"# Then upload your test suite to the opened Giskard server\n",
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"\n",
"If you are using Google Colab and you want to install the Giskard server **locally**, you can run the Giskard server by executing this line in the terminal of your **local** machine (see the [documentation](https://docs.giskard.ai/en/latest/guides/installation_app/index.html)):\n",
"\n",
"> giskard server start\n",
"> giskard server start --version 2.0.0b4\n",
"\n",
"Once the Giskard server is running, from the same terminal on your **local** machine, you can run:\n",
"\n",
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2 changes: 1 addition & 1 deletion python-client/pyproject.toml
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Expand Up @@ -107,7 +107,7 @@ giskard = "giskard.cli:cli"
name = "giskard"
readme = "README.md"
license = { text = "Apache Software License 2.0" }
version = "2.0.0b3"
version = "2.0.0b4"
description = "The testing framework dedicated to ML models, from tabular to LLMs"
authors = [
{ name = "Giskard AI", email = "hello@giskard.ai" },
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