Coobiw/ChartMoE_Reproduced

<div align='center'> <h1>This is a reproduction of ChartMoE according to its official github repo, which has better performance on ChartQA(with/without PoT).</h1> </div>

<p align="center"> <b><font size="6">ChartMoE</font></b> <p> <p align="center"> <b><font size="4">ICLR2025 Oral </font></b> <p>

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Project Page

Github Repo

Paper

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ChartMoE is a multimodal large language model with Mixture-of-Expert connector, based on InternLM-XComposer2 for advanced chart 1)understanding, 2)replot, 3)editing, 4)highlighting and 5)transformation.

Import from Transformers

To load the ChartMoE model using Transformers, use the following code:

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.

Open Source License

The code is licensed under Apache-2.0.