#Querrying
Oh! I'll have to note your press because I'm about to start querrying! #horrorwriterschat
April 16, 2025 at 6:05 PM
#kidlitchat my plan is to keep self-publishing my spooky MG series while querrying a different, unrelated spooky MG book 😅
May 7, 2025 at 2:00 AM
Argh, I can't figure out how to identify which of my posts you're replying to, so I don't know what you're querrying!
October 31, 2025 at 12:59 AM
Do you like character driven war stories? Do you like Steam Punk?
Do you like grounded magic systems?

Steam Company will def. scratch those interests, as soon as I get an agent. Follow along to see when it happens.

#Writing #booksky #Querrying
June 13, 2026 at 2:21 AM
That sweet moment when you cold email a researcher querrying for potential data and you get a positive response. Rare moment of academia happiness in this 2025
February 26, 2025 at 7:19 PM
Set up a writing only email account
1) less chance of losing responses to spam
2) separation so you only need to see rejections on your terms
3) if it saves drafts like Gmail you can keep all your querrying info in drafts. I had one for my letter, one for my synopsis, a 1 ch sample, 3 ch sample etc
What's a tip to pro authors you don't often see? I'll go first.

Come up with an explict file naming system that is easy for the other person to understand.

❌ headshot.jpg
✔️ CLPolk headshot by photographer name.jpg

❌ The Colony.docx
✔️ 20240521 CLPolk The Colony A Novel.docx

underscore optional
May 22, 2024 at 10:08 AM
I have read the thing now.

I wish I had not.

IDK why I thought it would get better. I doubt this thing would have made it past querrying on it's own merit.
Did I just buy a used book that I have a free e-arc copy of?

Yes. Yes, I did.

Did I also DNF that e-arc after the prologue because it was painfully lacking in editing.

Also yes.

Buuut

... now I can make a video about how the trad pub industry thinks books for young women don't require editing.
September 18, 2026 at 10:55 PM
Got more writing done, not a ton of words, but did complete Chapter 3 of my horror novel - a prequel to the novel I’m querrying! How is everyone else doing for #Novelnovember #novnov ?
November 20, 2025 at 2:06 AM
🚨 The second part of the tutorial series on mimimalistic LLMs integration in web environment is here! 🎉

🎬️ youtu.be/yNKYJzlKxh0

🧵1/n
Minimalistic LLMs streaming querrying integration into WebPage
YouTube video by Nicolay Rusnachenko
youtu.be
December 15, 2025 at 10:17 PM
So querrying is pretty straight forward, I guess I had bad experience working with FLask and trying for hours to get he connection working with SQLchemestry or smth like that. Or I was just not lucky.
November 24, 2025 at 3:35 PM
SYCL device info free_memory wrong on 2-stack PVC1550 GPU
Hello, in short, in SYCL, when querrying the amount of free memory on a GPU using the function dev.get_info<sycl::ext::intel::info::device::free_memory>() it is reported wrong. The function always reports the amount of free memory on the first stack in the 2-stack GPU, regardless if the sycl::device corresponds to the first or the second stack. I use export ZE_FLAT_DEVICE_HIERARCHY="FLAT" so the 2-stack GPU corresponds to two sycl::devices available to the user, one for each stack. I use PVC1550 GPUs on a private instance on the Tiber devcloud. icpx version 2025.0.1 I see the issue with lower icpx versions too (you might need to use `export ZES_ENABLE_SYSMAN=1` with the lower versions to enable the free memory querry) Reproducer code: #include <cstdio> #include <cstdlib> #include <vector> #include <sycl/sycl.hpp> int main(int argc, char ** argv) { if(argc <= 1) throw std::runtime_error("not enough arguments"); int gpu_idx = atoi(argv[1]); std::vector<sycl::device> gpus_all = sycl::device::get_devices(sycl::info::device_type::gpu); std::vector<sycl::device> gpus_levelzero; for(sycl::device & gpu : gpus_all) { if(gpu.get_backend() == sycl::backend::ext_oneapi_level_zero) { gpus_levelzero.push_back(gpu); } } printf("There are %zu levelzero GPUs\n", gpus_levelzero.size()); for(size_t i = 0; i < gpus_levelzero.size(); i++) { sycl::device & d = gpus_levelzero[i]; size_t mem_capacity = d.get_info<sycl::info::device::global_mem_size>(); size_t mem_free = d.get_info<sycl::ext::intel::info::device::free_memory>(); printf(" GPU %2zu: capacity = %12zu B = %6zu MiB, free = %12zu B = %6zu MiB\n", i, mem_capacity, mem_capacity >> 20, mem_free, mem_free >> 20); } sycl::queue q(gpus_levelzero[gpu_idx]); size_t allocsize = (size_t{60} << 30); void * ptr = sycl::malloc_device(allocsize, q); printf("Allocated on GPU %2d: %zu B = %zu MiB, ptr = %p\n", gpu_idx, allocsize, allocsize >> 20, ptr); printf("Current free memory:\n"); for(size_t i = 0; i < gpus_levelzero.size(); i++) { sycl::device & d = gpus_levelzero[i]; size_t mem_free = d.get_info<sycl::ext::intel::info::device::free_memory>(); printf(" GPU %2zu: free = %12zu B = %6zu MiB\n", i, mem_free, mem_free >> 20); } sycl::free(ptr, q); printf("Memory freed\n"); printf("Current free memory:\n"); for(size_t i = 0; i < gpus_levelzero.size(); i++) { sycl::device & d = gpus_levelzero[i]; size_t mem_free = d.get_info<sycl::ext::intel::info::device::free_memory>(); printf(" GPU %2zu: free = %12zu B = %6zu MiB\n", i, mem_free, mem_free >> 20); } return 0; } It finds all level zero GPU devices and reports their memory capacity and free memory. It then allocates 60 GiB of memory on a given GPU. Then it again prints the amount of free memory on each GPU. At the end it frees the memory and again reports the free memory on each GPU. Compile with icpx -fsycl source.cpp -o program.x and run as ./program.x <device_index_where_to_allocate> output with `./program.x 0` (or any other even number lower than number of gpus) (shortened): There are 16 levelzero GPUs GPU 0: capacity = 68719476736 B = 65536 MiB, free = 68673966080 B = 65492 MiB GPU 1: capacity = 68719476736 B = 65536 MiB, free = 68673966080 B = 65492 MiB GPU 2: capacity = 68719476736 B = 65536 MiB, free = 68673970176 B = 65492 MiB GPU 3: capacity = 68719476736 B = 65536 MiB, free = 68673970176 B = 65492 MiB ... Allocated on GPU 0: 64424509440 B = 61440 MiB, ptr = 0xff00000000200000 Current free memory: GPU 0: free = 4119027712 B = 3928 MiB GPU 1: free = 4119027712 B = 3928 MiB GPU 2: free = 68547817472 B = 65372 MiB GPU 3: free = 68547817472 B = 65372 MiB ... Memory freed Current free memory: GPU 0: free = 4119089152 B = 3928 MiB GPU 1: free = 4119142400 B = 3928 MiB GPU 2: free = 68548362240 B = 65372 MiB GPU 3: free = 68548427776 B = 65372 MiB ... You see, I allocated 60 GiB only on GPU 0, but GPU 1 also reports lower free memory. output with `./program.x 1` (or any other odd number lower than number of gpus) (shortened): There are 16 levelzero GPUs GPU 0: capacity = 68719476736 B = 65536 MiB, free = 68673966080 B = 65492 MiB GPU 1: capacity = 68719476736 B = 65536 MiB, free = 68673966080 B = 65492 MiB GPU 2: capacity = 68719476736 B = 65536 MiB, free = 68673974272 B = 65492 MiB GPU 3: capacity = 68719476736 B = 65536 MiB, free = 68673974272 B = 65492 MiB ... Allocated on GPU 1: 64424509440 B = 61440 MiB, ptr = 0xff00000000200000 Current free memory: GPU 0: free = 68543537152 B = 65368 MiB GPU 1: free = 68543537152 B = 65368 MiB GPU 2: free = 68547821568 B = 65372 MiB GPU 3: free = 68547821568 B = 65372 MiB ... Memory freed Current free memory: GPU 0: free = 68543533056 B = 65368 MiB GPU 1: free = 68543533056 B = 65368 MiB GPU 2: free = 68548452352 B = 65372 MiB GPU 3: free = 68548493312 B = 65372 MiB ... Here, I allocated 60 GiB on GPU 1, but the free memory function reports that almost all the memory is still free. Furthermore (this is probably a separate issue), after I free the memory using sycl::free, querrying the free device memory still treats is as allocated -- see the last group of free memory reports in the outputs. Link to docs about the device hierarchy: https://www.intel.com/content/www/us/en/docs/oneapi/optimization-guide-gpu/2025-0/exposing-the-device-hierarchy.html Am I doing something wrong? Is this expected on the 2-stack GPU? Can this be fixed? Thanks, Jakub
community.intel.com
November 25, 2024 at 6:22 PM
Could be all sorts of problems. Missing indexes, querrying a badly performing view or strange partitioning and of course making stuff up.
We can only guess.
March 22, 2025 at 7:37 PM
📢 I've tried #NovitaAI for querrying large datasets

novita.ai/models/model...

✅ ️Pros: support for OpenAI API is highgly convenient

❌️ Cons: The rate limit (20 Req/min) was a blocker for efficient batch processing; this is too impractical

🌟 In few lines: github.com/nicolay-r/bu...
March 6, 2026 at 1:18 PM
But I'm starting to doubt its even possible. I've stopped querrying for the time being to rework it with sections like this:

This book isn’t meant to make you appear normal. It’s not even meant to help you fit in or mask or join the mainstream.

⬇️
November 22, 2024 at 4:49 PM
The re-query behavior was happening _for every single set of changes_, causing lots of unnecessary work. Re-querrying now waits half a second before actually re-requesting the query. Should have don this from the get-go!
April 18, 2025 at 1:42 PM