Note about LLM not working now successfully added!

app.py

@@ -28,7 +28,7 @@ with block:
     # Topic modeller
     Generate topics from open text in tabular data, based on [BERTopic](https://maartengr.github.io/BERTopic/). Upload a data file (csv, xlsx, or parquet), then specify the open text column that you want to use to generate topics. Click 'Extract topics' after you have selected the minimum similar documents per topic and maximum total topics. Duplicate this space, or clone to your computer to avoid queues here!
     
-    Uses fast TF-IDF-based embeddings by default, which are fast but not very performant in terms of cluster. Change to [BAAI/bge-small-en-v1.5](https://huggingface.co/BAAI/bge-small-en-v1.5) model embeddings on the options page for topics of much higher quality, but slower processing time. If you have an embeddings .npz file previously made using this model, you can load this in at the same time to skip the first modelling step. If you have a pre-defined list of topics for zero-shot modelling, you can upload this as a csv file under 'I have my own list of topics...'. Further configuration options are available under the 'Options' tab. Topic representation with LLMs currently based on [StableLM-2-Zephyr-1.6B-GGUF](https://huggingface.co/second-state/stablelm-2-zephyr-1.6b-GGUF).
+    Uses fast TF-IDF-based embeddings by default, which are fast but not very performant in terms of cluster. Change to [BAAI/bge-small-en-v1.5](https://huggingface.co/BAAI/bge-small-en-v1.5) model embeddings on the options page for topics of much higher quality, but slower processing time. If you have an embeddings .npz file previously made using this model, you can load this in at the same time to skip the first modelling step. If you have a pre-defined list of topics for zero-shot modelling, you can upload this as a csv file under 'I have my own list of topics...'. Further configuration options are available under the 'Options' tab. Topic representation with LLMs currently based on [StableLM-2-Zephyr-1.6B-GGUF](https://huggingface.co/second-state/stablelm-2-zephyr-1.6b-GGUF) - this works locally, but unfortunately this doesn't yet seem to work on the Huggingface website, I'm working on it!
 
     I suggest [Wikipedia mini dataset](https://huggingface.co/datasets/rag-datasets/mini_wikipedia/tree/main/data) for testing the tool here, choose passages.parquet.
     """)