PaiDxng
16 minutes ago
The hardest part isn’t payment; the prompt itself may identify you. For truly sensitive topics, I’d abstract the details first, then use a local model—or avoid an LLM entirely.
Item id: 48885422
16 minutes ago
The hardest part isn’t payment; the prompt itself may identify you. For truly sensitive topics, I’d abstract the details first, then use a local model—or avoid an LLM entirely.
2 hours ago
With llama.cpp, Intel i9-13900KS CPU, 96 GB RAM, RTX 4070 running locally.
The models I'm using right now with that are:
gpt-oss-120b-F16.gguf
Qwen_Qwen3.5-27B-Q4_K_M.gguf
Qwen3.6-35B-A3B-UD-Q5_K_XL.gguf
gemma-4-31B-it-UD-Q6_K_XL.gguf3 hours ago
Maybe try Ollama Cloud, Prompt or response data is never logged or trained on:
4 hours ago
I spin up a gpu instance in a cloud, run my model via vllm, connect to it via an ssh tunnel. done.
3 hours ago
Can you elaborate on the first step? Which cloud and which service? What's the cost outlay if you are just having a convo and not doing anything 'agentic'?
3 hours ago
Hey sure.
It depends, but usually spin up an h100 on lambda.ai or coreweave. They have capacity and their UIs/APIs are nice. I spin it up for an hour or two, believe it was 6~ dollars an hour.
Once the gpu instance is up, you need to run vllm and a model, ie https://docs.lambda.ai/education/large-language-models/deplo....
Then you can connect your pi.dev, openwebui, etc etc to vllm and interact with it like normal.
35 minutes ago
I don't
2 hours ago
i've been using OpenAI's os PII-masking model, works decently and lightweight enough to run virtually anywhere https://huggingface.co/openai/privacy-filter
4 hours ago
Can't you do it logged out?
3 hours ago
With a local one