Feat: minor docs improvements for RLHF and faq on embeddings (#2401) [skip ci]

* feat: add doc on shrink_embeddings and custom calling

* chore: rename inference doc

* fix: clarify same config is used for all cli

* chore: rearrange order inference qmd

* feat: add simpo to doc

* fix: update defaults

* feat: add rl configs to doc

* fix: ensure beta consistent with trl.beta

* fix: clarify about lora/fft

* chore: rename title

* chore: fix language

* feat: move config reference higher

* Update docs/getting-started.qmd

Co-authored-by: salman <salman.mohammadi@outlook.com>

* Update docs/rlhf.qmd

Co-authored-by: salman <salman.mohammadi@outlook.com>

---------

Co-authored-by: salman <salman.mohammadi@outlook.com>

docs/faq.qmd

@@ -27,6 +27,16 @@ description: Frequently asked questions
 
 > A: This is usually an issue with the GPU. This can be resolved through setting the os environment variable `CUDA_VISIBLE_DEVICES=0`. If you are on runpod, this is usually a pod issue. Starting a new pod should take care of it.
 
+**Q: Received mismatch error on merge adapters / loading adapters between torch.Size of checkpoint and model.**
+
+> A: This is likely due to vocab size mismatch. By default, Axolotl expands the model's embeddings if the tokenizer has more tokens than the model. Please use the `axolotl merge-lora` command to merge the adapters instead of using your own scripts.
+
+> On the other hand, if the model has more tokens than the tokenizer, Axolotl does not shrink the model's embeddings unless `shrink_embeddings: true` is set in the config.
+
+**Q: How to call Axolotl via custom python scripts?**
+
+> A: Yes, since Axolotl is just Python, please see `src/axolotl/cli/main.py` on how each command is called.
+
 ### Chat templates
 
 **Q: `jinja2.exceptions.UndefinedError: 'dict object' has no attribute 'content' / 'role' / ____`**