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Training and Testing YOLO-NAS on Custom Dataset
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🎥 Watch as we take YOLO-NAS on a learning journey, training it on our unique dataset, then putting it to the ultimate test on unseen data. Let's see what it can uncover! #MachineLearning #datasethttps://t.co/nwjwchGYqK#objectdetection #ai #computervision #deeplearning… pic.twitter.com/Uo8KhRai9k
— Satya Mallick (@LearnOpenCV) 5 juin 2023Watch as we take YOLO-NAS on a learning journey, training it on our unique dataset, then putting it to the ultimate test on unseen data. Let's see what it can uncover! #MachineLearning #dataset https://
youtube.com/watch?v=vfQYRJ
1x4Qg
… #objectdetection #ai #computervision #deeplearning -
Deterministic Triggers vs Agent-Driven Event Handling
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probably something different. these are triggered deterministically, you probably want something like you described to be triggered as needed by the agent
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LangChain Prompt Composition Features for Reusability
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Python Documentation: https://
python.langchain.com/en/latest/modu
les/prompts/prompt_templates/examples/prompt_composition.html
… JS/TS Documentation: https://
js.langchain.com/docs/modules/p
rompts/prompt_templates/prompt_composition
… We want to make prompts as composable and reusable as possible – would love feedback on this implementation! -
PipelinePrompt: Sequencing Prompt Templates for AI Workflows
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The way this works is you define a `PipelinePrompt` with two components: – FinalPrompt: the final prompt template to be formatted
– PipelinePrompts: a sequence of tuples of (name, PromptTemplate) The `name` argument is how the formatted prompt will be passed to future prompts -
Pipeline Prompt: Composing Reusable Prompt Pieces Together
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Composable Prompts Wouldn't it be nice if there was a way to compose prompts together, reusing pieces across prompts? In the newest Python and JS release there now is with `Pipeline Prompt`! Links
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GPTeam Deep Dive: Open Source Generative Agents Simulation
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GPTeam Deep Dive GPTeam by @itstimconnors and team is a fully OSS project building off of @joon_s_pk
's "Generative Agents" paper Vey excited to share a guest blog post be him, going into great detail as to how they build the complex simulation -
Core Stability vs Experimental Features in Software Development
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the core stuff is and will be even. some of the integrations wont be, and some of the experimental stuff wont be
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European Digital Sovereignty: Open Code and Decentralized Services
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Propuesta de digitalización democrática y soberana de @xnet
: Código público europeo (libre, auditable, fácilmente utilizable e interoperable) para los servicios esenciales Correo descentralizado Que la UE compre Firefox En @disruptores_inn https://
elespanol.com/invertia/disru
ptores-innovadores/politica-digital/europa/20230601/propuestas-digitalizacion-democratica-soberana-europa/767923371_0.html
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HQ-SAM: High Quality Segment Anything Model
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Segment Anything in High Quality
— AK (@_akhaliq) 5 juin 2023
paper page: https://t.co/IG4IAN4a4V
propose HQ-SAM, equipping SAM with the ability to accurately segment any object, while maintaining SAM's original promptable design, efficiency, and zero-shot generalizability. Our careful design reuses and… pic.twitter.com/6xG0FES7hvSegment Anything in High Quality paper page: https://
huggingface.co/papers/2306.01
567
… propose HQ-SAM, equipping SAM with the ability to accurately segment any object, while maintaining SAM's original promptable design, efficiency, and zero-shot generalizability. Our careful design reuses and