Separate model and feature support matrices by category (#1100)

Signed-off-by: Teresa Chen <boe20211@gmail.com>

Author: boe20211

.buildkite/README.md

@@ -24,7 +24,7 @@ To support this requirement, each model and feature will go through a series of
 TPU-optimized models are models we rewrite the model definition as opposed to using the model definition from the vLLM upstream. These models will go through benchmark on top of unit and integration (accuracy) tests. To add a TPU-optimized model to CI, model owners can use the prepared [add_model_to_ci.py](pipeline_generation/add_model_to_ci.py) script. The script will populate a buildkite yaml config file in the `.buildkite/models` directory; config files under this directory will be integrated to our pipeline automatically. The python script takes 2 arguments:
 - **--model-name**: this is the **full name** of your model on Hugging Face. Please ensure to use the **full name** (ex: `meta-llama/Llama-3.1-8B` instead of `Llama-3.1-8B`) or else we won't be able to find your model.
 - **--queue**: this is the queue you want to run on (ex: `tpu_v6e_queue`)
-- **--category**: this parameter allows you to set the model category, with the following options available: "text-only" or "multimodel".
+- **--category**: this parameter allows you to set the model category, with the following options available: "text-only" or "multimodel". (default: "text-only")
 
 ```bash
 python add_model_to_ci.py --model-name <MODEL_NAME> --queue <QUEUE_NAME>
@@ -39,7 +39,7 @@ In the generated yml file, there are three TODOs that will need your input:
 vLLM-native models are models using the model definition from the vLLM upstream. These models will not go through benchmark on our pipeline. To add a vLLM-native model to CI, model owners can use the prepared [add_model_to_ci.py](pipeline_generation/add_model_to_ci.py) script. The script will populate a buildkite yaml config file in the `.buildkite/models` directory; config files under this directory will be integrated to our pipeline automatically. The python script takes 3 arguments:
 - **--model-name**: this is the **full name** of your model on Hugging Face. Please ensure to use the **full name** (ex: `meta-llama/Llama-3.1-8B` instead of `Llama-3.1-8B`) or else we won't be able to find your model.
 - **--queue**: this is the queue you want to run on (ex: `tpu_v6e_queue`)
-- **--category**: this parameter allows you to set the model category, with the following options available: "text-only" or "multimodel".
+- **--category**: this parameter allows you to set the model category, with the following options available: "text-only" or "multimodel". (default: "text-only")
 
 ```bash
 python add_model_to_ci.py --model-name <MODEL_NAME> --queue <QUEUE_NAME> --type vllm-native
@@ -53,7 +53,7 @@ In the generated yml file, there are two TODOs that will need your input:
 To add a new feature to CI, feature owners can use the prepared [add_feature_to_ci.py](pipeline_generation/add_feature_to_ci.py) script. The script will populate a buildkite yaml config file in the `.buildkite/features` directory; config files under this directory will be integrated to our pipeline automatically. The python script takes 2 arguments:
 - **--feature-name**: this is the name of your feature
 - **--queue**: this is the queue you want to run on (ex: `tpu_v6e_queue`)
-- **--category**: this parameter allows you to set the feature category, with the following options available: "feature support matrix" or "kernel support matrix".
+- **--category**: this parameter allows you to set the feature category, with the following options available: "feature support matrix" or "kernel support matrix". (default: "feature support matrix")
 
 ```bash
 python add_feature_to_ci.py --feature-name <FEATURE_NAME> --queue <QUEUE_NAME>