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IDEA-FinAI
/
chartmoe

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Transformers
PyTorch
chartmoe
feature-extraction
custom_code
Model card Files
xet
 Community
2
How to use from
vLLM
Install from pip and serve model 
# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "IDEA-FinAI/chartmoe"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "IDEA-FinAI/chartmoe",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'
Use Docker 
docker model run hf.co/IDEA-FinAI/chartmoe
Quick Links

ChartMoE

ICLR2025 Oral

arXiv

Project Page

Github Repo

Hugging Face Dataset

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.

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Paper for IDEA-FinAI/chartmoe