🔄 In a Training Loop

Dean Byrne PRO

Quazim0t0

24 7 92

https://huggingface.co/DaisyChainAI

AI & ML interests

DaisyChainAI🌼 / SmallLM's / San Francisco / Open Source

Recent Activity

liked a model about 6 hours ago

GODELEV/Rose-1.5-Medium

updated a model about 10 hours ago

Quazim0t0/Byrne-100M-Ultra-MC

reacted to robtacconelli's post with 🔥 about 10 hours ago

🧩 Ever dreamed of parallel programming in a few clicks? Tolquane: draw a Python pipeline in your browser, run it on threads, processes or a cluster - and it never hangs What if high-performance computing started with placing blocks - and the result stayed plain Python you can run anywhere? Tolquane is a library of composable building blocks (nodes, pipelines, farms, all-to-all, feedback loops) with a web editor on top. One graph, four runtimes: threads, child processes, coroutines, TCP across machines. Every channel is bounded, every deadlock is reported by name, every error cancels the run. What's inside - Tolquane Web: a canvas that writes the Python file, and a code editor that redraws the canvas. Run a flow and watch items, queue depth and busy time on every stage; tap any edge to see what flows through it. - AI builder: describe the flow in one sentence; it writes, checks, runs and improves it, you apply the diff. - Schedules with cron presets, webhooks, mail and retries. Git history of every flow. Users and roles. - `tq.optimize` fuses stages into farm ends and cuts threads; `tolquane launch` starts every host from one deploy file. Numbers: 5.5× on 8 workers for CPU-bound Python (processes runtime), 5.6× on free-threaded 3.14t, 1M items over TCP in 3.5 s. 🌐 Try it now, nothing to install (sign in as demo / tolquane): https://huggingface.co/spaces/robtacconelli/tolquane 💻 Code: https://github.com/robtacconelli/Tolquane 📦 pip install "tolquane[web]" && tolquane web 📚 Docs: https://robtacconelli.github.io/Tolquane/ Apache-2.0, Python 3.11+, no dependencies for the library itself. Try it, break it, tell me what you'd build with it - ⭐ appreciated!

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It feels like a sugar rush… this golden ratio they found. Stepping through a maze of processes, landing on what aims to be a generalist, raised from the cemetery of echoes of our thoughts, statements, findings, and conclusions. I never really thought beyond this point. I always assumed that the world would look as elegant as the innovations we create. I thought it would look different, have a defining design that really embodied the point we have now arrived at. I can't tell the difference. Everything looks the same. I think that's why it's even harder sometimes for us to swallow what is actually happening, because every representation that we've had from science fiction doesn't really fit the theme.

I don't really see any worry with text and language. These models can generalize them well, and we have all seen how profound it can be. What I do worry about more is when we leave the tiny world of language and replace it with the big world of experiences. What would it be like to generalize hundreds of lifetimes? Would it see the nuances better than I? Could it predict what comes next if it had enough data from observing and experiencing the world?...

Read more: https://huggingface.co/blog/Quazim0t0/little-world-big-world