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Fix style lint, add to indexes
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Signed-off-by: jphillips <josh.phillips@fearnworks.com>
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fearnworks committed Oct 20, 2024
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2 changes: 1 addition & 1 deletion docs/cookbook/atomic_caption.md
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## Conclusion
The transformers_vision module in Outlines provides a powerful way to work with vision-language models. It allows for structured generation of outputs that combine image analysis with natural language processing, opening up possibilities for complex tasks like detailed image captioning, visual question answering, and more.

By leveraging the capabilities of models like Pixtral-12B and the structured output generation of Outlines, you can create sophisticated applications that understand and describe visual content in a highly structured and customizable manner.
By leveraging the capabilities of models like Pixtral-12B and the structured output generation of Outlines, you can create sophisticated applications that understand and describe visual content in a highly structured and customizable manner.
1 change: 1 addition & 0 deletions docs/cookbook/index.md
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- [Knowledge Graph Generation](knowledge_graph_extraction.md): Generate a Knowledge Graph from unstructured text using JSON-structured generation.
- [Chain Of Thought (CoT)](chain_of_thought.md): Generate a series of intermediate reasoning steps using regex-structured generation.
- [ReAct Agent](react_agent.md): Build an agent with open weights models using regex-structured generation.
- [Vision-Language Models](atomic_caption.md): Use Outlines with vision-language models for tasks like image captioning and visual reasoning.
1 change: 1 addition & 0 deletions mkdocs.yml
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- Structured Generation Workflow: cookbook/structured_generation_workflow.md
- Chain of Thought (CoT): cookbook/chain_of_thought.md
- ReAct Agent: cookbook/react_agent.md
- Vision-Language Models: cookbook/atomic_caption.md
- Run on the cloud:
- BentoML: cookbook/deploy-using-bentoml.md
- Cerebrium: cookbook/deploy-using-cerebrium.md
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