Faster Whisper Gradio Real-time speech-to-text application using Faster Whisper with Gradio. This application utilizes DeeplX for translation.
SOFTWARE
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openai-gradio: Simplified Web Apps with OpenAI API
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openai-gradio a Python package that makes it very easy for developers to create web apps that are powered by @OpenAI API in a few lines of code pip install openai-gradio
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Flowise Workflow Powers OpenAI Realtime Console Integration
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This is all powered by a Flowise workflow that has access to tools: – search_web by @searxng – retriever_tool
– code_interpreter by @e2b_dev All you need is just a single function change on the client.addTools() in the demo repo: https://
github.com/FlowiseAI/open
ai-realtime-console
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PyTorch’s Functional Interface Design Evolution History
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fun fact: nn.functional wasn't part of the first design, and not part of the first 4 pre-releases; but then @szagoruyko5 convinced us that the functional interface in twitter/torch-autograd (in lua) was really nice to use for certain kinds of research; and that we must have
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Keras fit() automatic data prefetching and asynchronous logging optimization
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This isn't obvious. Most people remember to do data prefetching, but few do asynchronous logging. Keras `fit()` does both out of the box automatically, regardless of your data source. This gets you fully compact train_step stacking, like here — zero idle time.
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Seamless device sync without WiFi setup friction
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They could just magically appear on my phone, why do I need to even sync or deal with WiFi join dialogs.
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Apple’s Locked OS Limits Glasses User Experience
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Glasses would be SO much better if Apple’s OS would be locked down less. The flow to transfer pictures alone.
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OrCam: On-Device AI Processing for Visually Impaired Users
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Yep, def dual use. @OrCam is one example of a product made for visually impaired folks. Does all the processing on device too.
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Xcode AI Assistance: Debugging and Error Correction with Screenshots
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I've been dumping everything into Xcode and just asking it to create the edits in chunks that I can drop in manually, but it's harder to debug if it can't see everything. It seems to accept screenshots of the Xcode errors and produce corrected segments well.
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Using AI and screenshots to debug Xcode errors manually
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I've been dumping everything into Xcode and just asking it to create the edits in chunks that I can drop in manually, but it's harder to debug if it can't see everything. It seems to accept screenshots of the Xcode errors and produce corrected segments well.