LQK — BabyLM 2026 Strict
LQK is a 116M-parameter causal model built on a Llama-1-style decoder with Qwen3-Next-style gated attention and Kimi Attention Residuals (AttnRes). This seed-1337 model was trained for 10 epochs on the official BabyLM 2026 Strict data with its exact 16k byte-level BPE tokenizer.
Load with AutoModelForCausalLM.from_pretrained("ypwhere/LQK-BabyLM-Strict", trust_remote_code=True). The repository provides main plus the 28 required chck_*M checkpoint revisions. Training-data terms remain governed by the BabyLM release; the included nanoGPT-derived model code is provided for research reproducibility.
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Install from pip and serve model
# Install vLLM from pip: pip install vllm# Start the vLLM server: vllm serve "ypwhere/LQK-BabyLM-Strict"# Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "ypwhere/LQK-BabyLM-Strict", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'