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BDivyesh/boomi-stage-a-1.5b
into its Apache-2.0 base Qwen2.5-Coder-1.5B and quantizing to Q8_0 (~1.65 GB).llama-cpp-python runs it on a free 2-vCPU CPU much faster than full-precision
transformers, and a JSON grammar (GBNF) guarantees the output is always valid SPEC JSON.1from huggingface_hub import hf_hub_download
2from llama_cpp import Llama, LlamaGrammar
3path = hf_hub_download("BDivyesh/boomi-stage-a-1.5b-gguf", "boomi-stage-a-1.5b-q8_0.gguf")
4llm = Llama(model_path=path, n_ctx=2048, n_threads=2)
5# Prompt: BOOMI ChatML (system = stage_a_common.SYSTEM_PROMPT, user = the description).
6# Constrain to a single JSON object so the output is always a valid SPEC, then feed it
7# to the CP-SAT solver -> editable DXF.Qwen/Qwen2.5-Coder-1.5B (Apache-2.0). LoRA SFT on ResPlan (MIT) + RERA-derived
Indian per-dwelling rows (PII-stripped, geometry-only) + grammar captions. Fully permissive.
Drafts only — not for sanction/construction without licensed review.