Corrected Quick Start Instructions and Author Links

README.md

@@ -1805,7 +1805,7 @@ model-index:
 
 # lodestone-base-4096-v1
 
-[Hum-Works/lodestone-base-4096-v1](https://huggingface.co/Hum-Works/lodestone-base-4096-v1). [Griffin McCauley](https://www.linkedin.com/in/griffin-mccauley-187b6423a), [Will Fortin](https://huggingface.co/willathum), [Dylan DiGioia](https://huggingface.co/dylanAtHum) 2023
+[Hum-Works/lodestone-base-4096-v1](https://huggingface.co/Hum-Works/lodestone-base-4096-v1). [Griffin McCauley](https://huggingface.co/gmccaul1), [Will Fortin](https://huggingface.co/willathum), [Dylan DiGioia](https://huggingface.co/dylanAtHum) 2023
 
 This new [sentence-transformers](https://www.SBERT.net) model from [Hum](https://www.hum.works/) maps long sentences & paragraphs to a 768 dimensional dense vector space and can be used for tasks like clustering or semantic search.
 
@@ -1829,7 +1829,7 @@ Then you can use the model like this:
 ```python
 from sentence_transformers import SentenceTransformer
 
-model = SentenceTransformer('lodestone-base-4096-v1', trust_remote_code=True, revision='v1.0.0')
+model = SentenceTransformer('Hum-Works/lodestone-base-4096-v1', trust_remote_code=True, revision='v1.0.0')
 sentences = ["This is an example sentence", "Each sentence is converted"]
 embeddings = model.encode(sentences)
 print(embeddings)