appv⦿id
3.1K posts


@trekedge @NousResearch do open weights? no need to pay compute bills
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@GoingParabolic That's a forth dimensional image. Think about it as an 3D object which timeline is collapsing onto itself.
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How to Claude Code Yolo
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1. Rent a ~$4/month server from Hertzner
2. Install Tailscale on the VPS and on your Mac (you'll need to expose a UDP port on the VPS for Hertzner) [optional, or just ssh into the VPS]
3. Log in via ssh through tail scale, and set up a non-root user (Anthropic blocks --dangerously-skip-permissions on root)
4. Install a safety hook to avoid dangerous commands - npx claude-code-templates@latest --hook=security/dangerous-command-blocker --yes
5. Github setup: Create a fine-grained PAT with read/write on contents and pull requests for specific repos only! Then protect your main branch with a required PR rule. This way Claude can push to any feature branch freely, but can't land directly on main.
Then - to do data prep and train or evaluate voice models - asr or tts...
6. Set your HF token on studio . trelis . com and get a spend-limited API key to put into environment variables on the VPS.
Claude Code can then call the Studio API to trigger training runs, pull datasets, and run evals — all autonomously.
7. Optionally, add a Trelis Router (router . trelis . com) api key to your Trelis Studio account so you can evaluate proprietary models.
Finally - in the server - you can run:
alias yolo='claude --dangerously-skip-permissions'
then
tmux new -s yolo
yolo
and you'll start off a claude session where it will run without permissions
just close the terminal to leave it run, or press Ctrl+b and then d to detach from tmux. 'tmux attach -t yolo' to reconnect later.
---
for more, check "studio . trelis . com/yolo"

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@cosyposter I'm pretty sure that in our persue of exotic flavors we spread sneaky cancer from time to time without realizing it
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@Kekius_Sage As far as I know the path gets stretched which makes light take more time to reach the other side
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@COFFINHEAD1 @yacineMTB The only rich people will be the ones with robots powered by AGI and beyond
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Someone open-sourced a tool that REMOVES LLM CENSORSHIP in 45 minutes 🤯
It’s called Heretic. Instead of fighting with complex prompts to bypass safety filters, you run one single command and it permanently deletes the model's ability to refuse a prompt.
• Fully automatic (Zero config required)
• Preserves the model's raw intelligence
• Works on Llama, Qwen, Gemma, and dozens of others
• Runs locally on consumer hardware
100% Open Source.

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I don't trust Qwen models, even the large ones. I trust small ones even less.
Qwen has been benchmaxing its models since the very beginning, so the benchmark performance of a 4B parameter model beating Gemini 2.5 Flash Lite is most likely just the benchmark performance only.
4B is just not enough to store any general intelligence because most of the parameters will still be used to store facts. Well, not facts, but something that remains of them.

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@paneerchilli65 Looks so cool, I wonder if a planning mechanism (looking ahead in the future) could help
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run 2.2->
diffusion steps T = 30, 10k steps, 500 tiny stories, gen_len = 256
paneerchilli65@paneerchilli65
first try of making a micro-diffusion llm trained on shakespeare text for 5k steps with char level tokenizer
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