Update README.md

README.md

@@ -74,6 +74,7 @@ inference:
 - all the parameters for generation on the API are the same as [the base model](https://huggingface.co/pszemraj/led-base-book-summary) for easy comparison between versions.
 - works well on lots of text, can hand 16384 tokens/batch.
 
+> Note: the API is set to generate a max of 64 tokens for runtime reasons, so the summaries may be truncated (depending on length of input text). For best results use python as below.
 
 ---
 
@@ -82,7 +83,6 @@ inference:
 - it is recommended to use `encoder_no_repeat_ngram_size=3` when calling the pipeline object to improve summary quality.
   - this param forces the model to use new vocabulary and create an abstractive summary, otherwise it may compile the best _extractive_ summary from the input provided.
 - create the pipeline object:
-> Note: the API is set to generate a max of 64 tokens for runtime reasons, so the summaries may be truncated (depending on length of input text). For best results use python as below.
 
 ```
 from transformers import AutoModelForSeq2SeqLM, AutoTokenizer