Updating Model Card

README.md

@@ -11,7 +11,7 @@ library_name: transformers
 
 Databricks’ Dolly, a large language model trained on the [Databricks Machine Learning Platform](https://www.databricks.com/product/machine-learning), demonstrates that a 
 two-years-old [open source model](https://huggingface.co/EleutherAI/gpt-j-6B) can, when subjected to just 30 minutes of fine tuning on a focused corpus of 50k records 
-([Stanford Alpaca](https://crfm.stanford.edu/2023/03/13/alpaca.html)), exhibit surprisingly high quality instruction following behavior not characteristic of the foundation 
+([Stanford Alpaca](https://crfm.stanford.edu/2023/03/13/alpaca.html)), exhibits surprisingly high quality instruction following behavior not characteristic of the foundation 
 model on which it is based.  We believe this finding is important because it demonstrates that the ability to create powerful 
 artificial intelligence technologies is vastly more accessible than previously realized.
 
@@ -39,7 +39,7 @@ competitively with more modern model architectures or models subject to larger p
 
 The Dolly model family is under active development, and so any list of shortcomings is unlikely to be exhaustive, but we include known limitations and misfires here as a means to document and share our preliminary findings with the community.  
 In particular, `dolly-v1-6b` struggles with: syntactically complex prompts, programming problems, mathematical operations, factual errors, 
-dates and times, open-ended question answering, hallucination, enumerating lists of specific length, stylistic mimicry, etc.
+dates and times, open-ended question answering, hallucination, enumerating lists of specific length, stylistic mimicry, having a sense of humor, etc.
 
 ## Training Data, Bias & Objectionable Content
 Like all language models, `dolly-v1-6b` reflects the content and limitations of its training corpuses.