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
Eval Results
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, AutoModelForMultimodalLM tokenizer = AutoTokenizer.from_pretrained("ByteDance/Dolphin") model = AutoModelForMultimodalLM.from_pretrained("ByteDance/Dolphin", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- 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
Add Real5-OmniDocBench evaluation results for Dolphin
#10
by changdazhou - opened
.eval_results/real5_omnidocbench.yaml
ADDED
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- dataset:
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id: PaddlePaddle/Real5-OmniDocBench
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task_id: overall
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value: 61.78
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source:
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url: https://paddle-model-ecology.bj.bcebos.com/PPOCRVL/AIStudio/real5_omnidocbench/leaderboard_data.json
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name: Real5-OmniDocBench leaderboard data
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user: PaddlePaddle
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notes: Dolphin; official Real5-OmniDocBench result
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- dataset:
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id: PaddlePaddle/Real5-OmniDocBench
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task_id: scanning
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value: 72.16
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source:
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url: https://paddle-model-ecology.bj.bcebos.com/PPOCRVL/AIStudio/real5_omnidocbench/leaderboard_data.json
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name: Real5-OmniDocBench leaderboard data
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user: PaddlePaddle
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notes: Dolphin; official Real5-OmniDocBench result
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- dataset:
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id: PaddlePaddle/Real5-OmniDocBench
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task_id: warping
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value: 60.35
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source:
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url: https://paddle-model-ecology.bj.bcebos.com/PPOCRVL/AIStudio/real5_omnidocbench/leaderboard_data.json
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name: Real5-OmniDocBench leaderboard data
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user: PaddlePaddle
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notes: Dolphin; official Real5-OmniDocBench result
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- dataset:
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id: PaddlePaddle/Real5-OmniDocBench
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task_id: screen_photography
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value: 64.29
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source:
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url: https://paddle-model-ecology.bj.bcebos.com/PPOCRVL/AIStudio/real5_omnidocbench/leaderboard_data.json
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name: Real5-OmniDocBench leaderboard data
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user: PaddlePaddle
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notes: Dolphin; official Real5-OmniDocBench result
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- dataset:
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id: PaddlePaddle/Real5-OmniDocBench
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task_id: illumination
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value: 67.29
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source:
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url: https://paddle-model-ecology.bj.bcebos.com/PPOCRVL/AIStudio/real5_omnidocbench/leaderboard_data.json
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name: Real5-OmniDocBench leaderboard data
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user: PaddlePaddle
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notes: Dolphin; official Real5-OmniDocBench result
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- dataset:
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id: PaddlePaddle/Real5-OmniDocBench
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task_id: skew
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value: 44.83
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source:
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url: https://paddle-model-ecology.bj.bcebos.com/PPOCRVL/AIStudio/real5_omnidocbench/leaderboard_data.json
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name: Real5-OmniDocBench leaderboard data
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user: PaddlePaddle
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notes: Dolphin; official Real5-OmniDocBench result
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