BuildEng is an AI assistant. It should not replace professional engineering judgment, real site inspections, licensed structural assessments, or local building codes.

Use it as support, not as final authority.

Base Model

Qwen2.5-1.5B-Instruct

Fine-tuned by

Irfan Uruçi

Why this version?

Higher precision than INT4
Still small and efficient
Good choice when quality matters more than smallest size

Installation

pip install "optimum-intel[openvino]" openvino transformers

Usage

python

from optimum.intel.openvino import OVModelForCausalLM
from transformers import AutoTokenizer

model_id = "Irfanuruchi/qwen2.5-1.5b-buildeng-openvino-int8"

tokenizer = AutoTokenizer.from_pretrained(model_id)
model = OVModelForCausalLM.from_pretrained(model_id, device="CPU", compile=True)

messages = [
    {"role": "system", "content": "You are BuildEng. Give concise, inspection-first building engineering guidance."},
    {"role": "user", "content": "A homeowner reports diagonal cracks near a window corner. What should be inspected first?"}
]

prompt = tokenizer.apply_chat_template(messages, tokenize=False, add_generation_prompt=True)
inputs = tokenizer(prompt, return_tensors="pt")

output = model.generate(**inputs, max_new_tokens=160, do_sample=False)
new_tokens = output[0][inputs["input_ids"].shape[-1]:]

print(tokenizer.decode(new_tokens, skip_special_tokens=True))

Devices

CPU
GPU
NPU, where supported by OpenVINO and the system

Other Formats

Format	Repository
Hugging Face	`Irfanuruchi/qwen2.5-1.5b-buildeng`
GGUF	`Irfanuruchi/qwen2.5-1.5b-buildeng-GGUF-Q4_K_M`
MLX 4-bit	`Irfanuruchi/qwen2.5-1.5b-buildeng-mlx-4bit`
MLX 8-bit	`Irfanuruchi/qwen2.5-1.5b-buildeng-mlx-8bit`
OpenVINO INT4	`Irfanuruchi/qwen2.5-1.5b-buildeng-openvino-int4`

Built by Irfan Uruçi
Computer Engineer