Update depth-guided stable diffusion example to diffusers 0.27.2 (rer…

…un-io#5985)

### What
Closes rerun-io#5976 

### Checklist
* [x] I have read and agree to [Contributor
Guide](https://github.com/rerun-io/rerun/blob/main/CONTRIBUTING.md) and
the [Code of
Conduct](https://github.com/rerun-io/rerun/blob/main/CODE_OF_CONDUCT.md)manifest_url=https://app.rerun.io/version/main/examples_manifest.json)
* Using full set of examples from `nightly` build:
[rerun.io/viewer](https://rerun.io/viewer/pr/5985?manifest_url=https://app.rerun.io/version/nightly/examples_manifest.json)
* [x] The PR title and labels are set such as to maximize their
usefulness for the next release's CHANGELOG

- [PR Build Summary](https://build.rerun.io/pr/5985)
- [Recent benchmark results](https://build.rerun.io/graphs/crates.html)
- [Wasm size tracking](https://build.rerun.io/graphs/sizes.html)

To run all checks from `main`, comment on the PR with `@rerun-bot
full-check`.

examples/python/depth_guided_stable_diffusion/README.md

@@ -40,10 +40,10 @@ rr.log("prompt/uncond_input/ids", rr.Tensor(uncond_input.input_ids))
 ```
 
 ### Text embeddings
-Visualizing the text embeddings. The text embeddings are generated in response to the specific prompts used while the unconditional text embeddings represent a neutral or baseline state without specific input conditions.
+Visualizing the text embeddings (i.e., numerical representation of the input texts) from the prompt and negative prompt.
 ```python
-rr.log("prompt/text_embeddings", rr.Tensor(text_embeddings))
-rr.log("prompt/uncond_embeddings", rr.Tensor(uncond_embeddings))
+rr.log("prompt/text_embeddings", rr.Tensor(prompt_embeds))
+rr.log("prompt/negative_text_embeddings", rr.Tensor(negative_prompt_embeds))
 ```
 
 ### Depth map