Visual Question Answering
Transformers
Safetensors
Chinese
English
qwen3_vl
image-text-to-text
Docision
document-understanding
candidate-scoring
qwen3-vl
Instructions to use SoMarkAI/Docision-1.0 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use SoMarkAI/Docision-1.0 with Transformers:
# Use a pipeline as a high-level helper # Warning: Pipeline type "visual-question-answering" is no longer supported in transformers v5. # You must load the model directly (see below) or downgrade to v4.x with: # pip install "transformers<5.0.0" from transformers import pipeline pipe = pipeline("visual-question-answering", model="SoMarkAI/Docision-1.0")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForMultimodalLM processor = AutoProcessor.from_pretrained("SoMarkAI/Docision-1.0") model = AutoModelForMultimodalLM.from_pretrained("SoMarkAI/Docision-1.0", device_map="auto") - Notebooks
- Google Colab
- Kaggle
docs: align license description with GitHub
Browse files
README.md
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The bridge connects to a running Docision model service. Document and export paths belong to the MCP host; the model runs on the service host. See the [MCP setup instructions](https://github.com/SoMarkAI/docision/blob/main/docs/python-package.md#mcp) for prerequisites and remote GPU connections.
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<p align="center"><a href="https://github.com/SoMarkAI/docision/blob/main/LICENSE">Apache-2.0</a></p>
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The bridge connects to a running Docision model service. Document and export paths belong to the MCP host; the model runs on the service host. See the [MCP setup instructions](https://github.com/SoMarkAI/docision/blob/main/docs/python-package.md#mcp) for prerequisites and remote GPU connections.
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<p align="center"><a href="https://github.com/SoMarkAI/docision/blob/main/LICENSE">Apache-2.0</a> — A custom license based on Apache 2.0.</p>
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