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Add ClearML Serving examples list (#230)

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@ -215,7 +215,7 @@ that you will be able to visualize on Grafana.
:::info time-series values
You can also log time-series values with `--variable-value x2` or discrete results (e.g. classifications strings) with
`--variable-enum animal=cat,dog,sheep`. Additional custom variables can be added in the preprocess and postprocess with
a call to `collect_custom_statistics_fn({'new_var': 1.337})`. See [`preprocess_template.py`](https://github.com/allegroai/clearml-serving/blob/main/clearml_serving/preprocess/preprocess_template.py).
a call to `collect_custom_statistics_fn({'new_var': 1.337})`. See [preprocess_template.py](https://github.com/allegroai/clearml-serving/blob/main/clearml_serving/preprocess/preprocess_template.py).
:::
With the new metrics logged, you can create a visualization dashboard over the latency of the calls, and the output distribution.
@ -234,5 +234,17 @@ With the new metrics logged, you can create a visualization dashboard over the l
:::note
If not specified all serving requests will be logged, which can be changed with the `CLEARML_DEFAULT_METRIC_LOG_FREQ`
environment variable. For example `CLEARML_DEFAULT_METRIC_LOG_FREQ=0.2` means only 20% of all requests will be logged.
You can also specify per-endpoint log frequency with the `clearml-serving` CLI. See [`clearml-serving metrics`](clearml_serving_cli.md#metrics)
You can also specify per-endpoint log frequency with the `clearml-serving` CLI. See [clearml-serving metrics](clearml_serving_cli.md#metrics)
:::
## Further Examples
See examples of ClearML Serving with other supported frameworks:
* [Scikit-Learn](https://github.com/allegroai/clearml-serving/blob/main/examples/sklearn/readme.md) - random data
* [Scikit-Learn Model Ensemble](https://github.com/allegroai/clearml-serving/blob/main/examples/ensemble/readme.md) - random data
* [XGBoost](https://github.com/allegroai/clearml-serving/blob/main/examples/xgboost/readme.md) - iris dataset
* [LightGBM](https://github.com/allegroai/clearml-serving/blob/main/examples/lightgbm/readme.md) - iris dataset
* [PyTorch](https://github.com/allegroai/clearml-serving/blob/main/examples/pytorch/readme.md) - mnist dataset
* [TensorFlow/Keras](https://github.com/allegroai/clearml-serving/blob/main/examples/keras/readme.md) - mnist dataset
* [Model Pipeline](https://github.com/allegroai/clearml-serving/blob/main/examples/pipeline/readme.md) - random data