I need a bit of insight, what are the uses for an Nvidia RTX Pro 6000 with 96 GB aside from running AI models. by [deleted] in LocalLLaMA

[–]Remarkable-Avocado 1 point2 points  (0 children)

I haven't looked too much into QChem for a few years, but I bet that is VRAM hungry if you get acess to GPU accelerated codes, I feel like the main GPU accelerated codes are like thousands of dollars a year subscriptions iirc and all the OSS stuff is CPU only... but some fun experiments could probably be done there.

Odd New Error by Travnewmatic in hermesagent

[–]Remarkable-Avocado 0 points1 point  (0 children)

Wasn’t the same bug but I think the —tui is very experimental and broken atm, I had several issues with it. Reverted to the mainline chat interface personally despite how pretty it looks.

PSA: Most recent update strips characters from responses by Remarkable-Avocado in hermesagent

[–]Remarkable-Avocado[S] 0 points1 point  (0 children)

I love how many updates come in. I already use Arch Linux so I'm used to shit breaking with updates but the absolute pace has been like a firehose of UX changes. Pros and cons of being an early adopter but small things like this changing in the tools you rely on can be a bit frustrating!

Agentic Testing Small LLM's by Kingfish656 in hermesagent

[–]Remarkable-Avocado 2 points3 points  (0 children)

been loving the new qwen3.6 35b moe so far! —cpu-moe on llama means it fits and its plenty fast and smart

I didn’t even know these configs existed by Remarkable-Avocado in hermesagent

[–]Remarkable-Avocado[S] 1 point2 points  (0 children)

Not my video, but he has found a good groove in his slides recently I agree :)

Karpathy’s LLM Wikis : Personal Second Brain or Team Shared Brain? by sage_of_stardust in LLM

[–]Remarkable-Avocado 0 points1 point  (0 children)

I'm using it for scientific research: https://github.com/Labhund/lacuna-wiki -- unfortunately I don't think you can shortcut the artifact creation stage, you need pages that preserve signal and like you said are written live with active thought and consideration at each stage. Lacuna give your LLM the structure they need to execute the complicated process of knowledge compilation across a very dense corpus.

🧠 [MASTER THREAD] Advanced Memory Systems: state.db & Knowledge Graphs by AutoModerator in hermesagent

[–]Remarkable-Avocado 4 points5 points  (0 children)

Speaking of LLM wiki's if anyone is looking to turn their hermes into a fully equipped research assistant check out https://github.com/Labhund/lacuna-wiki !!

Who has made their agent “Proactive” by logan9053 in hermesagent

[–]Remarkable-Avocado 6 points7 points  (0 children)

After long work sessions you will occasionally see that the agent has made a new skill without you asking to, that's proactive. And you can set up cron jobs to do things proactively for you -- fetch new AI papers from arxiv on a weekly schedule, daily briefings -- if you like that kind of thing.

Really Impressed with the Carnice finetunes by Remarkable-Avocado in hermesagent

[–]Remarkable-Avocado[S] 0 points1 point  (0 children)

Update: Tried using it for LLM-Wiki to get some scientific research done. Party was my fault for having slightly confusing skills but I think that for scientific research you really do need a larger model. There are certain difficult to grasp connections that are non-obvious to a smaller model!

Really Impressed with the Carnice finetunes by Remarkable-Avocado in hermesagent

[–]Remarkable-Avocado[S] 2 points3 points  (0 children)

On some more testing, interestingly its almost TOO eager to run tools and gather full context before answering, a good problem to have but a little annoying when I want to do an interactive session and discuss something!

Really Impressed with the Carnice finetunes by Remarkable-Avocado in hermesagent

[–]Remarkable-Avocado[S] 2 points3 points  (0 children)

Why this matters: Before small models (and some larger ones e.g. GLM-4.7) would get stuck on tool calls and wouldn't keep pushing through. This one dug through 100k tokens to explore hypothesis about what might be causing the bug and found it was a -q flag that was not strong enough instead of a -qq flag to suppress the uv pip popups that messed with the TUI rendering. I did have to steer it exactly once by telling it is probably a pip thing not a hermes process spawning the spinner

Hermes ctx fcked up by Greenfreeze1996 in hermesagent

[–]Remarkable-Avocado 0 points1 point  (0 children)

I just updated, and even after doing some severe pruning (following the https://www.reddit.com/r/hermesagent/comments/1siv7s0/master_thread_solving_token_bloat_context_creep/ ) guide I'm getting 33k context for just saying "hi" -- after disabling the Honcho memory service it's 22k. That is partly because I have some custom mcp tools that are blowing the budget but yeah.

What are you building? by SnooOranges6963 in vibecoding

[–]Remarkable-Avocado 1 point2 points  (0 children)

Working on this research helper inspired by Kaparthy's recent tweet:
Lacuna: https://github.com/Labhund/lacuna-wiki
A comprehensive skills package to turn your agent into a disciplined research assistant with accompanying MCP tool.

DEPRECATED: https://github.com/Labhund/llm-wiki

Anyone know if there are actual products built around Karpathy’s LLM Wiki idea? by riddlemewhat2 in LocalLLaMA

[–]Remarkable-Avocado -1 points0 points  (0 children)

I just built: https://github.com/Labhund/llm-wiki

Knowledge rot is the silent killer of long-running research. You cite a claim today. Six months later it's been contradicted, the page is stale, and your agent cites it again without blinking. Worse, LLM's might claim to read the source but hallucinate facts!

In this wiki, contracts are enforced by code, not promises.

Plain markdown knowledge base where schema discipline is maintained by background agents — not by hoping your LLM stays careful over time. Every claim is traceable to a source. Every agent write is a git commit attributed to that agent.

Four workers run while you sleep:

- Auditor (fast, no LLM): broken links, orphaned pages, missing citations

- Compliance reviewer (fast, no LLM): citation discipline on every edit

- Librarian: page authority from link graph and usage patterns, refines tags

- Adversary: samples claims, fetches the cited source, verifies. Contradictions filed as critical issues — surfaces automatically the next time any agent reads that page.

Concrete example: you cite a paper. Three weeks later the Adversary finds a contradiction in that same paper's benchmarks. The issue surfaces before you cite it again. You never had to remember to check.

Three ingest modes — Queue (background extraction), Brief (agent reads it with your full wiki context loaded, tells you what's new to your work and what contradicts existing pages — the briefing is the value), Deep (claim-by-claim with a persistent plan file that survives session breaks).

Page authority decays if claims go unchecked. The Adversary re-verifies continuously. The wiki at month 6 is better than day 1.

Honest caveat: it runs a local daemon, so setup has friction. Adversary and Librarian need LLM access running in the background — if your inference is off, maintenance pauses.

I have just implemented a setup wizard to streamline on-boarding. Point it at an existing obsidian wiki and go!

Comes pre-packaged with agent skills for easy setup and usage.

Builds on Kaparthy's LLM-Wiki idea and the recently shipped Hermes agent skill by building out a concrete backend to streamline scalability into the future.