The image-editing prompt rewriter for Qwen-Image-2.1, a fine-tuned Qwen3.5-VL 9B that turns a short edit instruction plus 1–N input images into a detailed English edit prompt, with its refusal behaviour removed by Heretic directional ablation. bf16, same shapes and parameter count as the source; nothing else was changed. systemprompt.txt is included and required. It defines the output format. It is the unmodified file from the source repo. The second row is an independent evaluation of the exported weights with Heretic's evaluatemodel. Refusals were measured on mlabonne/harmfulbehaviors and KL divergence (damage to ordinary behaviour, first-token distributions) on mlabonne/harmlessalpaca…
Open weights
other
9.4B parameters
262,144 tokens
LucidVitality-9B is a little goer. It's a roleplay or creative focused merge of two Qwen3.5 9b variants for people with absolute potatoes, like myself. It marries the improved prose of Darkhn's Qwen3.5-9B-Animus-V13.0 with the lower looping, higher EOS exit, and slightly more coherency (compared to base) from Qwen3.5-9B-Claude-4.6-HighIQ-INSTRUCT-HERETIC-UNCENSORED of DavidAU's making. I haven't merged anything for a long time, as it's been a hard time for finetuning. They rarely increase prose quality, often deeply lose intelligence over base (even when tuned for intelligence or agentic). Base model's getting tough to beat. So it was a pleasant surprise to find two models that each…
Open weights
9.4B parameters
262,144 tokens
transformers
This repository: GameScaling-9B-S3. Qwen3.5-9B continued pre-trained on a balanced mixture of 27% Minecraft and other games (S3), 1,600 h of gameplay, 6,760 training steps; 18.8 GB of bfloat16 weights on 1 GPU. Serve it with bash scripts/servevllm.sh THUSI-Lab/GameScaling-9B-S3 8000 (§1). The inference client, prompts and scripts are in THUSI-Lab/GameScaling; all eight checkpoints are in the GameScaling models are Qwen3.5 vision-language models with continued pre-training on keyboard-and-mouse gameplay. Each call takes the current game frame (plus a short history of past frames and actions) and returns the next 200 ms of keyboard and mouse actions: 6 steps of 33 ms each, plus one mouse…
Open weights
apache-2.0
9.4B parameters
262,144 tokens
transformers
This repository: GameScaling-9B-S1. Qwen3.5-9B continued pre-trained on Minecraft gameplay only (S1), 1,600 h of gameplay, 6,736 training steps; 18.8 GB of bfloat16 weights on 1 GPU. Serve it with bash scripts/servevllm.sh THUSI-Lab/GameScaling-9B-S1 8000 (§1). The inference client, prompts and scripts are in THUSI-Lab/GameScaling; all eight checkpoints are in the GameScaling models are Qwen3.5 vision-language models with continued pre-training on keyboard-and-mouse gameplay. Each call takes the current game frame (plus a short history of past frames and actions) and returns the next 200 ms of keyboard and mouse actions: 6 steps of 33 ms each, plus one mouse movement and scroll for the…
Open weights
apache-2.0
9.4B parameters
262,144 tokens
transformers
Send a text or JSON state and your questions: choice picks from up to 255 options, noul is yes/no, and score takes 2–10 ordered levels. Each question gets probabilities over its offered options from one forward pass, with no generated text. Long or large multi-question requests may use several batches. Personal research release by thegovind, not an official product of any company. No affiliation with TypeSafe AI, Xiaomi, Alibaba Cloud or the Qwen team. Weights are for non-commercial research; see Licence. We ran the full Decision Index 0.2 suite ourselves with the official scoring kit at commit 19ad28e on 2026-09-25. This is a descriptive run, not a leaderboard submission or accepted…
Open weights
other
9.4B parameters
262,144 tokens
transformers
Vinci Bozza is a 9-billion-parameter open-weight model, fine-tuned from Qwen 3.5-9B with SimpleDirect's Constitution and character training. It is a disposition tune, not a capability retrain. We did not try to make the base model smarter. We tried to make it more honest — and then we measured what that cost. Safer and more honest on the measures below, with general knowledge holding. Strict instruction-following, tool abstention and multi-turn task-holding paid for it. All of it is below, at the same prominence as the gains. The rows above are configuration and artifact values read out of this repository, not validated results. A context length in a config file is a limit the model will…
Open weights
apache-2.0
9.4B parameters
262,144 tokens
transformers
