cleanup kserve docs

demo/kserve/built-tip.md

@@ -3,37 +3,35 @@
 Caikit-TGIS image always requires a Caikit-formatted model. Below are the instructions from converting a model to a Caikit-formatted one.
 
 1. Clone the model repository (or have the model folder in a directory). In the below example, Bloom-560m model repo is cloned.
-~~~
+
+```bash
 yum -y install git git-lfs
 git lfs install
 git clone https://huggingface.co/bigscience/bloom-560m
-~~~
+```
 
-2. Clone the caikit-nlp repo:
-~~~
-git clone https://github.com/caikit/caikit-nlp.git
-~~~
+2. Create a virtual environment with Python 3.9 and install `caikit-nlp`
 
-3. Create a virtual environment with Python 3.9 and install the caikit-nlp
-~~~
-python3 -m virtualenv -p python3.9 venv
+````bash
+python3 -m venv -p python3.9 venv
 source venv/bin/activate
-python3.9 -m pip install ./caikit-nlp
-~~~
+python3.9 -m pip install git+https://github.com/caikit/caikit-nlp.git
+
+3. (Optional) Clone the `caikit-tgis-serving` repo, if not already available.
 
-4. (Optional) Clone the caikit-tgis-serving repo, if not already available.
-~~~
+```bash
 git clone https://github.com/opendatahub-io/caikit-tgis-serving.git
-~~~
+````
+
+4. Invoke the conversion script located in /utils of caikit-tgis-serving repo.
+
+```bash
+caikit-tgis-serving/utils/convert.py/ --model-path ./bloom-560m/ --model-save-path ./bloom-560m-caikit
+```
 
-5. Invoke the conversion script located in /utils of caikit-tgis-serving repo.
-~~~
-cp caikit-tgis-serving/utils/convert.py . 
-./convert.py --model-path ./bloom-560m/ --model-save-path ./bloom-560m-caikit
-~~~
+5. Move the model folder (ie. `/bloom-560m-caikit`) into desired storage (ie. S3, MinIO, PVC or other)
+6. Do **not** include the model folder name/directory directly in InferenceService, but rather point to the directory where the model folder is located. Let's say the `bloom-560m-caikit` directory is located at: `example-models/llm/models/bloom-560m-caikit/`, then `storageUri` value in the InferenceService CR should look like:
 
-6. Move the model folder (ie. `/bloom-560m-caikit`) into desired storage (ie. S3, MinIO, PVC or other)
-7. Do *not* include the model folder name/directory directly in InferenceService, but rather point to the directory where the model folder is located. Let's say the `bloom-560m-caikit` directory is located at: `example-models/llm/models/bloom-560m-caikit/`, then `storageUri` value in the InferenceService CR should look like:
-~~~
+```bash
 storageUri: s3://example-models/llm/models
-~~~
+```