Art10001
Art10001 t1_jecukzj wrote
Reply to [P] Introducing Vicuna: An open-source language model based on LLaMA 13B by Business-Lead2679
A Koala model is listed on the site. What is it?
Art10001 t1_jectiy3 wrote
Reply to [P] Introducing Vicuna: An open-source language model based on LLaMA 13B by Business-Lead2679
Soon: Huemul, Pudu, Condor.
Art10001 t1_jdmyazo wrote
Reply to comment by sweatierorc in [R] Reflexion: an autonomous agent with dynamic memory and self-reflection - Noah Shinn et al 2023 Northeastern University Boston - Outperforms GPT-4 on HumanEval accuracy (0.67 --> 0.88)! by Singularian2501
Quantum computing solves new types of problems, and their resolution, or findings from them, improves our lives.
Art10001 t1_jdmff0b wrote
Reply to comment by sweatierorc in [R] Reflexion: an autonomous agent with dynamic memory and self-reflection - Noah Shinn et al 2023 Northeastern University Boston - Outperforms GPT-4 on HumanEval accuracy (0.67 --> 0.88)! by Singularian2501
More intelligence, more time (AIs are at different time scales) = faster rate of discoveries
Art10001 t1_jdihrod wrote
Reply to comment by BullockHouse in [D] I just realised: GPT-4 with image input can interpret any computer screen, any userinterface and any combination of them. by Balance-
Probably. And if not, certainly someday.
Art10001 t1_jdd0ihw wrote
Reply to [P] New toolchain to train robust spiking NNs for mixed-signal Neuromorphic chips by FrereKhan
Great. Neuromorphic technology is genius (or at least cool) and very underappreciated.
Art10001 t1_jdd0ag1 wrote
Reply to comment by FrereKhan in [P] New toolchain to train robust spiking NNs for mixed-signal Neuromorphic chips by FrereKhan
Brainchip has 1 million neurons already. Loihi and Loihi2 similar.
Art10001 t1_jcy7rqs wrote
Reply to comment by pkuba208 in [Research] Alpaca 7B language model running on my Pixel 7 by simpleuserhere
Yes, that's why it was tried in a Pixel 7 which has 8 GB of RAM and maybe even swap.
Art10001 t1_jcy2sb5 wrote
Reply to comment by pkuba208 in [Research] Alpaca 7B language model running on my Pixel 7 by simpleuserhere
Raspberry Pi 4 is far slower than modern phones.
Also there was somebody else saying it probably actually uses 4/6 GB.
Art10001 t1_jcy2jck wrote
Reply to comment by ninjasaid13 in [Research] Alpaca 7B language model running on my Pixel 7 by simpleuserhere
I was asleep, my apologies for not replying earlier.
Run pacman -Syu then pacman -Sy build-essential then cd to the build directory and follow the instructions
Art10001 t1_jcwg7bv wrote
Reply to comment by ninjasaid13 in [Research] Alpaca 7B language model running on my Pixel 7 by simpleuserhere
Try installing MSYS2.
Art10001 t1_jcwg5zg wrote
Reply to comment by pkuba208 in [Research] Alpaca 7B language model running on my Pixel 7 by simpleuserhere
You can really see how phones defeat 10 year old computers, as revealed by their Geekbench 5 scores.
Art10001 t1_jcwg2pl wrote
Reply to comment by Taenk in [Research] Alpaca 7B language model running on my Pixel 7 by simpleuserhere
CoreML.
Please, review this link and associated research paper: https://github.com/apple/ml-ane-transformers
Art10001 t1_jcwfyw8 wrote
Reply to comment by baffo32 in [Research] Alpaca 7B language model running on my Pixel 7 by simpleuserhere
I heard MoE is bad. I have no sources sadly.
Art10001 t1_jcweykf wrote
Reply to comment by evangelion-unit-two in [R] ChatGLM-6B - an open source 6.2 billion parameter Eng/Chinese bilingual LLM trained on 1T tokens, supplemented by supervised fine-tuning, feedback bootstrap, and RLHF. Runs on consumer grade GPUs by MysteryInc152
> Any dispute arising from or in connection with this License shall be submitted to Haidian District People's Court in Beijing.
Art10001 t1_jcnv4te wrote
Reply to comment by hfnuser0000 in [D] PyTorch 2.0 Native Flash Attention 32k Context Window by super_deap
https://github.com/LagPixelLOL/ChatGPTCLIBot
There are other similar projects I found while trying to recover this one, which may also be of interest. You can find them by searching "chatgpt embeddings memory github"
Art10001 t1_jcnv4kf wrote
Reply to comment by KerfuffleV2 in [D] PyTorch 2.0 Native Flash Attention 32k Context Window by super_deap
https://github.com/LagPixelLOL/ChatGPTCLIBot
There are other similar projects I found while trying to recover this one, which may also be of interest. You can find them by searching "chatgpt embeddings memory github"
Art10001 t1_jcnakzz wrote
Reply to comment by KerfuffleV2 in [D] PyTorch 2.0 Native Flash Attention 32k Context Window by super_deap
There is a github project that uses embeddings with GPT-3.5 to create infinite memory, as long as you have infinite disk space. The database grows and grows the more you talk.
Art10001 t1_jbjv13z wrote
Reply to comment by Pat3418 in [P] LazyShell - GPT based autocomplete for zsh by rumovoice
I once setup the smallest model of Pygmalion to act as a chatbot. The UI was premade and Gradio-based.
It worked well. I had tried Flan-T5 first, but the UI did not recognize the model kind (yet.)
Art10001 t1_jb176r8 wrote
Reply to comment by ThirdMover in [R] RWKV (100% RNN) can genuinely model ctx4k+ documents in Pile, and RWKV model+inference+generation in 150 lines of Python by bo_peng
Indeed.
Art10001 t1_jb172wo wrote
Reply to comment by royalemate357 in [R] RWKV (100% RNN) can genuinely model ctx4k+ documents in Pile, and RWKV model+inference+generation in 150 lines of Python by bo_peng
It once said 100 times faster and 100 times less (V)RAM here. However, it now says that RWKV-14B can be run with only 3 GB of VRAM, which is regardless a massive improvement, because a 14B model normally requires about 30 GB of VRAM or thereabouts.
Art10001 t1_jb0q49f wrote
Reply to [R] RWKV (100% RNN) can genuinely model ctx4k+ documents in Pile, and RWKV model+inference+generation in 150 lines of Python by bo_peng
If you are RWKV's creator, kudos to you, the work you have done is amazing.
Reminder for everybody: it can run rather quickly in CPU, meaning it can truly run locally in phones. It also is 100 times faster, and uses 100 times less (V)RAM.
Art10001 t1_jayg0yg wrote
Reply to comment by rumovoice in [P] LazyShell - GPT based autocomplete for zsh by rumovoice
SLA level of 99 % uptime/availability results in the following periods of allowed downtime/unavailability:
Daily: 14m 24s
Weekly: 1h 40m 48s
Monthly: 7h 14m 41s
Quarterly: 21h 44m 4.4s
Yearly: 3d 14h 56m 18s
Art10001 t1_jayfsfe wrote
Reply to comment by BeautifulLurker in [P] LazyShell - GPT based autocomplete for zsh by rumovoice
I've seen DM like 5 times in recent memory...
In reddit we use PM, Private Message. Not DM, Direct Message, which is a Discordism.
Art10001 t1_jegrlea wrote
Reply to [discussion] Anybody Working with VITMAE? by Simusid
Are you saying what you're making will create "artificial" birdsong, corresponding to "not real" species?