Instructions to use oroikon/ft_pix2struct_chart_captioning with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use oroikon/ft_pix2struct_chart_captioning with Transformers:

# Use a pipeline as a high-level helper
from transformers import pipeline

pipe = pipeline("image-text-to-text", model="oroikon/ft_pix2struct_chart_captioning")

# Load model directly
from transformers import AutoProcessor, AutoModelForImageTextToText

processor = AutoProcessor.from_pretrained("oroikon/ft_pix2struct_chart_captioning")
model = AutoModelForImageTextToText.from_pretrained("oroikon/ft_pix2struct_chart_captioning")

Notebooks
Google Colab
Kaggle
Local Apps

vLLM

How to use oroikon/ft_pix2struct_chart_captioning with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "oroikon/ft_pix2struct_chart_captioning"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "oroikon/ft_pix2struct_chart_captioning",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker

docker model run hf.co/oroikon/ft_pix2struct_chart_captioning

SGLang

How to use oroikon/ft_pix2struct_chart_captioning with SGLang:

Install from pip and serve model

# Install SGLang from pip:
pip install sglang
# Start the SGLang server:
python3 -m sglang.launch_server \
    --model-path "oroikon/ft_pix2struct_chart_captioning" \
    --host 0.0.0.0 \
    --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "oroikon/ft_pix2struct_chart_captioning",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker images

docker run --gpus all \
    --shm-size 32g \
    -p 30000:30000 \
    -v ~/.cache/huggingface:/root/.cache/huggingface \
    --env "HF_TOKEN=<secret>" \
    --ipc=host \
    lmsysorg/sglang:latest \
    python3 -m sglang.launch_server \
        --model-path "oroikon/ft_pix2struct_chart_captioning" \
        --host 0.0.0.0 \
        --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "oroikon/ft_pix2struct_chart_captioning",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Docker Model Runner
How to use oroikon/ft_pix2struct_chart_captioning with Docker Model Runner:
```
docker model run hf.co/oroikon/ft_pix2struct_chart_captioning
```

Create README.md

by khyeongkyun - opened Oct 26, 2023

base: refs/heads/main

←

from: refs/pr/1

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+16

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+---
+license: apache-2.0
+datasets:
+- hk-kaden-kim/pix2struct-chartcaptioning
+language:
+- en
+metrics:
+- bleu
+- meteor
+- rouge
+pipeline_tag: image-to-text
+tags:
+- graph
+- chart
+- caption
+---