Recent submissions

Comment · 2 years ago
HiddenBar
Comment · 2 years ago
This is old news
Comment · 3 years ago
Oh I see, my bad
Comment · 3 years ago
They did use the Canny ControlNet Pipeline
Comment · 3 years ago
I'm hitting 3.9tok/s with CTX of 300 tokens on Android/778G via Userland & this is with an older unoptimized build of llama.cpp
Comment · 3 years ago
Feels like there should be two branches of system design for unit profitable architecture for paying users vs VC backed architectures to support non-paying users.
Comment · 3 years ago
For long running stuff https://developer.apple.com/tutorials/app-dev-training/trans... should be straightforward to translate as well using ported on-device BERT models
Comment · 3 years ago
JM2C

lood_in_4bit=True will let you run Llama2-7B variants at 6.3GB VRAM.

Comment · 3 years ago
I'm building a tool for transcriptions where your brand, product or any other technical jargon or heck even your own name does not need a fine-tuned model all the time. Both as a free native Mac app & a SaaS tool for those who need to process in bulk. Hit me up at [email protected] to check it out, will launch as FortuneSpeech.com once out of beta.

Thanks to this post, I kind of have another idea for a 'corrections to transcript' feature that Llama2-7B even on CPU can help with.

Comment · 3 years ago
It's like a repeat of c++ or python. If you can find folks & tooling for what you want to accomplish then go for it. I don't think founders who actually have paying customers concern themselves with what works best per cent of compute spend rather what allows them to improve the product, while as an outsider it may seem that they can reduce costs by choosing X over Y.
Comment · 3 years ago
I would suggest getting your feet wet with HuggingFace Spaces free/Pro plan to get started & then their APIs once you get the hang of setting up things there. After that you can start with setting up LangChain pipelines or direct vector DB queries for which sort of columns or SQL queries to formulate(for the latter).

As for the former classifier you can try doing zero-shot classification between n number of categories + others. Models like Flan-T5/T5/Flan-UL2/DistillBART(also ~7B-40B param LLMs can also do this but would be overkill).

Comment · 3 years ago
You can always pull from the recovery/cloud of Apple. It's just an excuse to push you to newer hardware
Comment · 3 years ago
Another person actually tested out the bot & tried to search for a product called mCaffiene & instead whatever LLM they're using just changed it to McAfee anti-virus to try & answer the query. Pretty untested & thrown into the user's hands.
Comment · 3 years ago
Bring the calculator widget back cowards!
Comment · 3 years ago
Another person actually tested out the bot & tried to search for a product called mCaffiene & instead whatever LLM they're using just changed it to McAfee anti-virus to try & answer the query. Pretty untested & thrown into the user's hands

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