1 prompt, it spun up 4 subagents and died within 2 minutes, then pushed the $99/month plan. The prompt didn't even get to complete. This is so bad. I literally burned 53% weekly usage on a failed prompt in the span of 2 minutes.
This shit is getting cancelled.
Here's a list of ai novel writing harnesses I can think of off-hand:
(opensource) autonovel, storydaemon, long novel agent kit, novelclaw, authoragent
(paid) autofiction, novelcrafter, sudowrite, storybible, storyforge
Keep in mind these aren't 'roleplay harnesses' as such, they're designed to allow an AI to write a novel while staying coherent and true to traditional novel structures.
The Second Son of the House of Bells is a novel written by Claude in the autonovel harness by Nous Research (same people who made Hermes harness btw). It's the typical ~89k word novel
I wouldn't try to use them as-is as an RP harness but they have advanced 'narrative memory and good writing' tools that I think could be adapted for RP pretty easily if one was so inclined. Personally, I like training models more (particularly dataset prep, base model selection, making small models smarter; I'm pursuing a lot things here).
But, I'm curious since there's a TON of overlap between RP and novel writing interests, if maybe some of you are actively using AI novel writing harnesses or working on bridging them into something like ST or similar? And what are your thoughts?
Purple prose? High and tight? Low and crude? Verbose vs snappy? Examples would be great (DM if too spicy)
I've got Gemma 4 QAT in the oven right now and then Muse Glimmer next.
I have other model dataset+training planned but want to experiment a bit with tuning for specific narration styles that much of the community will resonate with. Models that run locally and already know what you like and how you like it 😉 ❤️
I would be grateful to hear what people like and fold that into my decision making as I tailor the dataset and model targets accordingly. 🙏
I've spent the last week finetuning DeepSeek V4 Flash 0731. The result is HeatSeeker, my first ever trained lora finetune for creative writing and roleplay. I basically wanted to take the intelligence, scene awareness, and consistency of a huge modern MoE and push it harder toward natural dialogue, character writing, long-form roleplay while staying coherent and interesting to talk to.
The training was done using Mswift and it took about 60 hours on a single rtx pro 6000 for a 27.5M token dataset, 4546 conversations. I put a LARGE amount of effort into unslopping for spelling, grammar, punctuation, etc.
And, genuinely it surprised me how well it turned out in terms of varied imaginative continuations and clean, coherent roleplay responses. Even without a system prompt, it defaults to a usual roleplay conversation style and I'm happy to share it with you all.
I did a "minimum viable potato" test on my lenovo legion 5i w/4070m and 128gb ram and get around 4.5 t/g. Not great, but usable lol. On a RTX Pro 6000, I get about 72 t/g.
This is my first model share and if there's any other details I forgot or questions you have, I'm happy to answer them.
Disclaimer: DeepSeek is not associated with me and the project inherits the original MIT license. Don't be a nuisance and please have fun chatting with my model. Feedback welcome!
Curious if the unsloth team will be have quants available for Tencent's Hy3 model (hopefully soon 👉👈) ? Saw it over in r/LocalLLaMA and looks very promising as a large local agent!
I'm always keeping an eye on competitive hardware and was looking at tenstorrent cards, particularly the p150a which while its memory bandwidth is only 512GB/s, it does have 32 GB of GDDR6 and a high-speed Ethernet fabric (4×800 GbE) so multi-card systems don't rely on PCIe alone. something like this is exciting because in 1 or 2 card generations they could potentially be a better local ai gpu than Nvidia or amd since its 1/3rd the price of a 5090 and has native GPU meshing (rip nvlink).
is anyone here is actually ruuning the p150a (or any other of their other cards) for local AI? How mature is the hardware + software stack currently? would you buy into the platform again?
