Update README.md

README.md

@@ -1,39 +1,40 @@
----
-license: apache-2.0
-pipeline_tag: visual-question-answering
----
-
-
-<p align="center">
-    <b><font size="6">ChartMoE</font></b> 
-<p>
-
-<div align="center">
-
-[Project Page](https://chartmoe.github.io/)
-
-[Github Repo](https://github.com/IDEA-FinAI/ChartMoE)
-
-</div>
-
-![](teaser.png)
-
-**ChartMoE** is a multimodal large language model with Mixture-of-Expert connector, based on [InternLM-XComposer2](https://github.com/InternLM/InternLM-XComposer/tree/main/InternLM-XComposer-2.0) for advanced chart understanding, translation and editing. 
-
-
-## Import from Transformers
-To load the ChartMoE model using Transformers, use the following code:
-```python
-import torch
-from transformers import AutoTokenizer, AutoModelForCausalLM
-ckpt_path = "IDEA-FinAI/chartmoe"
-tokenizer = AutoTokenizer.from_pretrained(ckpt_path, trust_remote_code=True)
-model = AutoModelForCausalLM.from_pretrained(ckpt_path, trust_remote_code=True).half().cuda().eval()
-```
-
-## Quickstart & Gradio Demo
-We provide a simple example and a gradio webui demo to show how to use ChartMoE. Please refer to [https://github.com/IDEA-FinAI/ChartMoE](https://github.com/IDEA-FinAI/ChartMoE).
-
-
-## Open Source License
+---
+license: apache-2.0
+pipeline_tag: visual-question-answering
+library_name: transformers
+---
+
+
+<p align="center">
+    <b><font size="6">ChartMoE</font></b> 
+<p>
+
+<div align="center">
+
+[Project Page](https://chartmoe.github.io/)
+
+[Github Repo](https://github.com/IDEA-FinAI/ChartMoE)
+
+</div>
+
+![](teaser.png)
+
+**ChartMoE** is a multimodal large language model with Mixture-of-Expert connector, based on [InternLM-XComposer2](https://github.com/InternLM/InternLM-XComposer/tree/main/InternLM-XComposer-2.0) for advanced chart understanding, translation and editing. 
+
+
+## Import from Transformers
+To load the ChartMoE model using Transformers, use the following code:
+```python
+import torch
+from transformers import AutoTokenizer, AutoModelForCausalLM
+ckpt_path = "IDEA-FinAI/chartmoe"
+tokenizer = AutoTokenizer.from_pretrained(ckpt_path, trust_remote_code=True)
+model = AutoModelForCausalLM.from_pretrained(ckpt_path, trust_remote_code=True).half().cuda().eval()
+```
+
+## Quickstart & Gradio Demo
+We provide a simple example and a gradio webui demo to show how to use ChartMoE. Please refer to [https://github.com/IDEA-FinAI/ChartMoE](https://github.com/IDEA-FinAI/ChartMoE).
+
+
+## Open Source License
 The code is licensed under Apache-2.0.