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ByteDance
/
Dolphin

Image-Text-to-Text
Transformers
Safetensors
Chinese
English
vision-encoder-decoder
document-parsing
document-understanding
document-intelligence
ocr
layout-analysis
table-extraction
multimodal
vision-language-model
Model card Files Files and versions
xet
Community
9

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

  • Libraries
  • Transformers

    How to use ByteDance/Dolphin with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("image-text-to-text", model="ByteDance/Dolphin")
    # Load model directly
    from transformers import AutoTokenizer, AutoModelForImageTextToText
    
    tokenizer = AutoTokenizer.from_pretrained("ByteDance/Dolphin")
    model = AutoModelForImageTextToText.from_pretrained("ByteDance/Dolphin")
  • Notebooks
  • Google Colab
  • Kaggle
  • Local Apps
  • vLLM

    How to use ByteDance/Dolphin with vLLM:

    Install from pip and serve model
    # Install vLLM from pip:
    pip install vllm
    # Start the vLLM server:
    vllm serve "ByteDance/Dolphin"
    # Call the server using curl (OpenAI-compatible API):
    curl -X POST "http://localhost:8000/v1/completions" \
    	-H "Content-Type: application/json" \
    	--data '{
    		"model": "ByteDance/Dolphin",
    		"prompt": "Once upon a time,",
    		"max_tokens": 512,
    		"temperature": 0.5
    	}'
    Use Docker
    docker model run hf.co/ByteDance/Dolphin
  • SGLang

    How to use ByteDance/Dolphin 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 "ByteDance/Dolphin" \
        --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": "ByteDance/Dolphin",
    		"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 "ByteDance/Dolphin" \
            --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": "ByteDance/Dolphin",
    		"prompt": "Once upon a time,",
    		"max_tokens": 512,
    		"temperature": 0.5
    	}'
  • Docker Model Runner

    How to use ByteDance/Dolphin with Docker Model Runner:

    docker model run hf.co/ByteDance/Dolphin
New discussion
Resources
  • PR & discussions documentation
  • Code of Conduct
  • Hub documentation

enable the usage on huggingface-inference-toolkit

#9 opened 10 months ago by
luquiT4

test

#8 opened 11 months ago by
shijre

There is a serious illusion problem in the recognition of complex layout images

1
#7 opened 11 months ago by
ranson

Congratulations on the Release and the Demo from Hugging Face

❀️πŸ”₯ 3
#6 opened 11 months ago by
reach-vb

How to get this model working with vLLM?

πŸ‘€πŸ”₯ 4
5
#5 opened 12 months ago by
ququwowo

onnx model

πŸ”₯ 1
2
#4 opened 12 months ago by
hzkitty

Dolphin

πŸ§ πŸ€— 3
#3 opened 12 months ago by
ehartford

Snippet and demo

πŸ”₯πŸ‘ 7
2
#2 opened 12 months ago by
merve

Github links in the readme are broken

πŸ‘ 1
2
#1 opened 12 months ago by
adi751
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