1.76× faster decoding on BF16, 1.65× on FP8, 1.51× on NVFP4. Agentic coding ~2.6×. Same outputs: exact rejection sampling. This is an early result, an improved version with higher acceptance is in training.
auto 200m 2 is out now! Auto is a series of models designed to classify if a tool called by an AI agent is safe to run or not, like how the "auto" approval modes work in codex or claude. This is the smallest model in the series by far and it still packs a punch! Over 96 percent accuracy on the held out benchmark, beating deepseek v4 0731 and absolutely destroying regex at classifying if a tool call is safe to run (to be fair it is a bit of a weird and very hard benchmark but it works!) check it out: ProCreations/auto-200m-2
Introducing Bonsai 2 27b GSQ RCO! It applies two newly-popular methods for quants to retain higher accuracy. Bonsai 2 27b GSQ RCO achieves around 6 percent lower perplexity on WikiText-2 compared to Bonsai 2 27b and roughly unchanged benchmark accuracy overall, with small mixed differences. It stays under 7gb, staying small like the original bonsai. Note that this is more of an experiment than a true finished product but the gains we saw are cool! Test it out and let me know what you think! ProCreations/bonsai-2-27b-gsq-rco-gguf
ICYMI: Grug 27b v2 released! It brings increased quality, fixes repetitive loop / malformed session title issues seen in grug 27b v1.1, and reasoning efforts now truly work. ProCreations/grug-27b-v2
check out ProCreations/booper-chat an extremely tiny LM that is surprisingly coherent at english and hilarious to chat with. space: ProCreations/booper-chat btw for the compute giveaway, winners have been decided. Booper is apart of this (won, they allowed the model to be posted on my page and they used it for their use case) and the other winners have been contacted. NOTE!! this model is trained purely as a conversationalist and do NOT depend on it for math, facts, and pretty much everything.
Last day to enter the compute giveaway i mentioned in my last post for your projects! https://giveaway.ssh.codes side note: i have a new x account, go follow it! https://x.com/SSHCodes with the x account i have big plans for ai stuff 👀
I have hit 300 followers, and I think this calls for a bit of a giveaway 👀 a unique one, too. I have had countless AI projects I have wanted to make but have been (brutally) blocked by compute. Now that I finally have just enough compute to sort of get around (i still don't have enough 😭) and for hitting 300 followers (tysm!) I will be funding three of the communities projects via HuggingFace jobs, giving them 150 dollars max worth of compute each. I will personally be picking the winners, I am looking for projects that genuinely hit the compute wall: great ideas, blocked by compute, just like the countless ideas I've had. To join, head over to https://giveaway.ssh.codes RULES: - Final result must be open weight or open source - Only one submission per person - Have fun!
grug 27b v1.1 is here! It is now based off Qwen 3.8 27b and comes with its reasoning efforts and is a solid trade off on grug 27b v1, coming with enhanced coding performance and agentic performance. Check it out! https://huggingface.co/ProCreations/Grug-27b-v1.1
i go to huggingface, look on spaces just to see whats new and i see that MY OWN space is trending. ProCreations/maple-webgpu very cool to see, on the very first page of spaces too. anything is possible in the open source community!
new day, new models! Introducing the Auto series, a series of classifiers for determining if agentic tool calls are safe to run or not to prevent any harmful actions from happening. They have high performance compared to other LLMs commonly used for this task with incredible speed and small memory footprints. ProCreations/auto-1b (recommended generally, much higher accuracy) ProCreations/auto-0.4b (faster but worse) Comes with datasets as well (open source ftw)! A GitHub repo with pi extensions etc will come soon with this model.
check out this cool webgpu thing i made! ProCreations/maple-webgpu runs this model deepgrove/maple-preview with cool performance i found today on WebGPU locally on your computer with very fast speeds. made with a mix of gpt 5.6 sol + opus 5 ultracode, its amazing what agents can do now, just a year ago this wouldve been impossible with them.
