Fix document link (microsoft#2126)

## Describe your changes
Fix document link
## Checklist before requesting a review
- [ ] Add unit tests for this change.
- [ ] Make sure all tests can pass.
- [ ] Update documents if necessary.
- [ ] Lint and apply fixes to your code by running `lintrunner -a`
- [ ] Is this a user-facing change? If yes, give a description of this
change to be included in the release notes.
- [ ] Is this PR including examples changes? If yes, please remember to
update [example
documentation](https://github.com/microsoft/Olive/blob/main/docs/source/examples.md)
in a follow-up PR.

## (Optional) Issue link

Author: devang-ml

docs/source/how-to/cli/cli-optimize.md

@@ -30,8 +30,8 @@ This command will quantize weights into int4 precision before converting the mod
 
 ## Customizing model optimization process
 
-`olive optimize` primarily requests desired model precision and intended ExecutionProvider that will be used to run the optimized model. Based on these information, `olive optimize` command will generate model optimiation recipe as per user request and execute the recipe to produce to output model. Advanced users can use `--dry_run` option to save the `config.json` file on the disk. See comprehensive list of [options](../reference/options.html) you can use to customize the model optimization process further by modifying the `config.json` file produced by the `olive optimize --dry_run ...` command.
+`olive optimize` primarily requests desired model precision and intended ExecutionProvider that will be used to run the optimized model. Based on these information, `olive optimize` command will generate model optimiation recipe as per user request and execute the recipe to produce to output model. Advanced users can use `--dry_run` option to save the `config.json` file on the disk. See comprehensive list of [options](../../reference/options.html) you can use to customize the model optimization process further by modifying the `config.json` file produced by the `olive optimize --dry_run ...` command.
 
 ## Additional details
 
-See `olive optimize` [reference](../reference/python_api.md#optimize) for the complete list of supported options.
+See `olive optimize` [reference](../../reference/python_api.md#optimize) for the complete list of supported options by this command.

docs/source/how-to/index.md

@@ -7,7 +7,7 @@
 
 The Olive CLI provides a set of primitives such as `quantize`, `finetune`, `onnx-graph-capture`, `auto-opt` that enable you to *easily* optimize select models and experiment with different cutting-edge optimization strategies without the need to define workflows.
 
--[How to use the `olive optimize` command to optimize a Pytorch model](cli/cli-optimize)
+- [How to use the `olive optimize` command to optimize a Pytorch model](cli/cli-optimize)
 - [How to use the `olive auto-opt` command to take a PyTorch/Hugging Face model and turn it into an optimized ONNX model](cli/cli-auto-opt)
 - [how to use the `olive finetune` command to create (Q)LoRA adapters](cli/cli-finetune)
 - [How to use the `olive quantize` command to quantize your model with different precisions and techniques such as AWQ](cli/cli-quantize)