Update README.md

README.md

@@ -12,7 +12,7 @@ pipeline_tag: text-generation
 
 [![Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/drive/1FEmlwGgn9209iQO-rs2-9UHPLoytwZMH?usp=sharing)
 
-This is an open‑source chart‑understanding Vision‑Language Model (VLM) developed at **Bespoke Labs** and maintained by **Liyan Tang** and **Bespoke Labs**. It sets a new state‑of‑the‑art in chart question‑answering (Chart‑QA) for 7 billion‑parameter models, outperforming much larger closed models such as Gemini‑1.5‑Pro and Claude‑3.5 on seven public benchmarks.
+This is an open‑source chart‑understanding Vision‑Language Model (VLM) developed at [Bespoke Labs](https://www.bespokelabs.ai/) and maintained by [Liyan Tang](https://www.tangliyan.com/) and Bespoke Labs. It sets a new state‑of‑the‑art in chart question‑answering (Chart‑QA) for 7 billion‑parameter models, outperforming much larger closed models such as Gemini‑1.5‑Pro and Claude‑3.5 on seven public benchmarks.
 
 Please check our blog for more information about how we trained the model <Blog Post Link>
 
@@ -112,7 +112,7 @@ llm = LLM(
 )
 
 # Running inference
-image_url = "https://github.com/bespokelabsai/chartqa-examples/blob/main/images/ilyc9wk4jf8b1.png?raw=true"
+image_url = "https://github.com/bespokelabsai/minichart-playground-examples/blob/main/images/ilyc9wk4jf8b1.png?raw=true"
 question = "How many global regions maintained their startup funding losses below 30% in 2022?"
 
 print("\n\n=================Model Output:===============\n\n", get_answer(image_url, question))