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reranking still worth it for small sets: setup advice - Printable Version +- Inference (https://www.datasculpting.ai/inference) +-- Forum: Training & Customization (https://www.datasculpting.ai/inference/forumdisplay.php?fid=13) +--- Forum: Dataset Creation / Curation (https://www.datasculpting.ai/inference/forumdisplay.php?fid=56) +--- Thread: reranking still worth it for small sets: setup advice (/showthread.php?tid=883) |
reranking still worth it for small sets: setup advice - mellowstream - 10-07-2026 I figured I'd ask here before changing everything. My current setup is llama.cpp with A6000, and I keep running into tool calling. If you've tested something similar, what did you keep and what did you stop bothering with? My use case is pretty ordinary: local chat, some document work, and occasional batch jobs. Re: reranking still worth it for small sets: setup advice - relaysupply90 - 10-07-2026 I don't think that's the whole story. The reported numbers can look compelling, but in ordinary usage I didn't see the same benefit. Could be a workload difference, but I wouldn't generalize too fast from one setup. Re: reranking still worth it for small sets: setup advice - mangopeak72 - 10-08-2026 I'd approach it in a boring order. If you're on LM Studio, I'd confirm the version first and then reduce variables until the behavior is obvious. Re: reranking still worth it for small sets: setup advice - edgekite - 10-11-2026 That matches what I was seeing. The pattern around long context has been pretty similar for me. Re: reranking still worth it for small sets: setup advice - benchplease - 10-11-2026 Good point. I don't think your conclusion is far off. Re: reranking still worth it for small sets: setup advice - northquill - 10-11-2026 Need a little more detail here. What model, what runtime, and roughly what context size? Re: reranking still worth it for small sets: setup advice - localcraft17 - 10-14-2026 Appreciate the detail. I ended up in about the same place using llama.cpp. Re: reranking still worth it for small sets: setup advice - quantghost - 10-14-2026 Quote:Appreciate the detail. I ended up in about the same place using llama.cpp. Not sure I agree there. I get why that seems right, but on 5090 the bottleneck felt elsewhere. Could be a workload difference, but I wouldn't generalize too fast from one setup. Re: reranking still worth it for small sets: setup advice - thetapath - 10-14-2026 My first guess would be this: Before rebuilding anything, I'd test one clean baseline with Mistral and compare from there. |