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Nymbo PRO

Nymbo

https://www.nymbo.net/

AI & ML interests

I like unrestricted, free, utilitarian stuff. I tend to archive good spaces because I don't trust y'all to keep them good :) Most spaces with runtime errors just need a restart. Paused spaces should work but require a GPU, duplicate to use.

Recent Activity

reacted to owensong's post with 🔥 33 minutes ago

I just released Inflect-Nano-v1, an ultra-small 4.63 parameter text-to-speech model. The main idea is simple: instead of only making the acoustic model tiny and relying on a larger external vocoder, Inflect-Nano-v1 keeps the complete text-to-waveform stack under 5M parameters. Quick facts: - 4.63M total inference parameters - 3.46M acoustic model - 1.17M vocoder - 24 kHz audio - English-only - Single male voice - Runs locally with a simple PyTorch inference script Why I made it: Most modern TTS models are much larger, and even many “small TTS” projects depend on a separate vocoder. I wanted to see how far a complete tiny TTS stack could be pushed while still producing usable speech. It is not SOTA, and I am not trying to claim it competes with large TTS systems. The interesting part is the size-to-functionality ratio. What works: It can generate arbitrary English speech locally, and the model is small enough to be interesting for: - local voice assistants - embedded/edge experiments - browser or WASM-style TTS exploration - efficient inference research - tiny-model baselines Limitations: The quality is still limited. It can sound robotic, stumble on difficult unseen text, and the vocoder is still a clear bottleneck. Long or unusual prompts are less reliable. So I would frame this as a research/demo release, not a production TTS engine. I’d love feedback from people interested in: - tiny speech models - vocoders - local TTS - efficient inference - embedded speech synthesis - improving small-model generalization If people find it useful, I’m interested in putting more training budget into a stronger v2. Model page: https://huggingface.co/owensong/Inflect-Nano-v1

updated a collection 33 minutes ago

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liked a model 33 minutes ago

owensong/Inflect-Nano-v1

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Post

7441

We should really have a release date range slider on the /models page. Tired of "trending/most downloaded" being the best way to sort and still seeing models from 2023 on the first page just because they're embedded in enterprise pipelines and get downloaded repeatedly. "Recently Created/Recently Updated" don't solve the discovery problem considering the amount of noise to sift through.

Slight caveat: Trending actually does have some recency bias, but it's not strong/precise enough.

Post

3483

Genuine recommendation: You should really use this AutoHotKey macro. Save the file as macros.ahk and run it. Before sending a prompt to your coding agent, press Ctrl + Alt + 1 and paste your prompt to any regular chatbot. Then send the output to the agent. This is the actual, boring, real way to "10x your prompting". Use the other number keys to avoid repeating yourself over and over again. I use this macro prolly 100-200 times per day. AutoHotKey isn't as new or hype as a lot of other workflows, but there's a reason it's still widely used after 17 years. Don't overcomplicate it.

; Requires AutoHotkey v1.1+

; All macros are `Ctrl + Alt + <variable>`

^!1::
    Send, Please help me more clearly articulate what I mean with this message (write the message in a code block):
return

^!2::
    Send, Please make the following changes:
return

^!3::
    Send, It seems you got cut off by the maximum response limit. Please continue by picking up where you left off.
return

In my experience the past few months, Ctrl + Alt + 1 works best with Instruct models (non-thinking). Reasoning causes some models to ramble and miss the point. I've just been using GPT-5.x for this.