metadata
license: apache-2.0
pipeline_tag: image-text-to-text
library_name: transformers
paper: https://arxiv.org/abs/2409.03277
This is a reproduction of ChartMoE according to its official github repo, which has better performance on ChartQA(with/without PoT).
ChartMoE
ICLR2025 Oral
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.