Update README.md

README.md

@@ -12,13 +12,30 @@ 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](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.
+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 six public benchmarks.
+
+1. **Blog Post**: https://www.bespokelabs.ai/blog/bespoke-minichart-7b
+2. **Model Playground**: https://playground.bespokelabs.ai/minichart
+---
+
+# Example Outputs
+
+Following are two examples of output obtained from Bespoke-MiniChart-7B
+
+
+<p align="left">
+    <img src="https://cdn-uploads.huggingface.co/production/uploads/6444e4417a7b94ddc2d14e1d/E5WGhi_fVNzCsrKeNeIs3.png" width="700">
+</p>
+
+<p align="left">
+    <img src="https://cdn-uploads.huggingface.co/production/uploads/6444e4417a7b94ddc2d14e1d/bYKXRm3sfOdX3zd_5qUpK.png" width="700">
+</p>
 
-Please check our blog for more information about how we trained the model <Blog Post Link>
 
 # Model Performance
 
-Our model achieves state-of-the-art performance on chart understanding among models with similar sizes. In addition to that, our models can even surpass closed-models such as Gemini-1.5-Pro and Claude-3.5.
+Bespoke-MiniChart-7B achieves state-of-the-art performance on chart understanding among models with similar sizes. In addition to that, the model can even surpass closed-models such as Gemini-1.5-Pro and Claude-3.5.
+
 
 | Model / Category                       | ChartQAPro (1637) | ChartQA (2500) | EvoChart (1250) | CharXiv (4000) | ChartX (1152) | ChartBench (2100) | MMC (808) | Average |
 |----------------------------------------|------------------:|---------------:|----------------:|---------------:|--------------:|------------------:|----------:|--------:|
@@ -42,6 +59,10 @@ Our model achieves state-of-the-art performance on chart understanding among mod
 
 # Model Use:
 
+The model is available on the playground here: https://playground.bespokelabs.ai/minichart
+
+You can also run the model with the following snippet: 
+
 ```python
 import requests
 from PIL import Image
@@ -118,6 +139,7 @@ question = "How many global regions maintained their startup funding losses belo
 print("\n\n=================Model Output:===============\n\n", get_answer(image_url, question))
 ```
 
+---
 # Licence
 
 This work is licensed under [CC BY-NC 4.0](https://creativecommons.org/licenses/by-nc/4.0/).