LangSmith Evaluations With the rapid pace of AI, developers are often faced with a paradox of choice: how to choose the right prompt, how to trade-off LLM quality vs cost? Evaluations can accelerate development with structured process for making these decisions. But, we've
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Integrating Gradio with OpenCV DNN for Real-Time Web Applications
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🚀 Blog-tastic Tuesdays 🚀https://t.co/CdPoepqAr1
— Satya Mallick (@LearnOpenCV) 9 avril 2024
Integrating Gradio with OpenCV DNN unlocks the answers to creating lightweight, efficient web applications that offer real-time inference capabilities. This combination leverages OpenCV’s robust deep-learning model inference… pic.twitter.com/Dh6zMih8rjBlog-tastic Tuesdays https://
learnopencv.com/integrating-gr
adio-with-opencv-dnn/
… Integrating Gradio with OpenCV DNN unlocks the answers to creating lightweight, efficient web applications that offer real-time inference capabilities. This combination leverages OpenCV’s robust deep-learning model inference -
Discrete Space Prompting vs Prefix Tuning Model Optimization
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well i'm pretty certain it all happens in *discrete* space, via prompting, and strings; prefix tuning requires training a model, taking gradients, dense parameters, etc.
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MLX and Tinygrad: Open Source ML Frameworks in Complexity Phase
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MLX is nice, early in its complexity phase.
also tinygrad. -
AI Session Ends Early: 800kLOC Written, Unexpected Termination Bug
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6 hours in, it self reports ~800 kLOC written (unclear if this includes core dump output, i bet it does) and then as I was typing this suddenly ended its session, well before its 24hr max runtime per session. it's not supposed to end this early and this is likely a bug. i've
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Small Models Utility in Unit Tests and Tiny Applications
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Small models are super useful for unit tests, tiny applications
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Command-line LLM usage and web UI development approach
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I've been focusing a great deal of effort on command-line LLM usage, partly because there's so little attention being paid to it by anyone else – which is weird because it's such a natural fit for how prompting works I do plan to add a web UI to my LLM tool at some point though
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Essential Python Function for AI Engineers
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Here is one of the most powerful and reusable functions you'll need as an AI engineer: “`
def remove_first_line(test_string): if test_string.startswith("Here") and test_string.split("n")[0].strip().endswith(":"): return re.sub(r'^.*n', '', test_string, count=1) -
Devin AI coding progress: 500 lines with unit testing guidance
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just checking back on it after a lovely dinner with @sgrove ~500LOC in and the unit testing seems to be guiding it well devin works on a queue so this is normal ish for about 2hrs of unsupervised ai coding