metadata
license: apache-2.0
language:
- en
tags:
- text-generation-inference
- transformers
- smolify
- dslm
pipeline_tag: text-generation
inference:
parameters:
temperature: 1
top_p: 0.95
top_k: 64
🤏 smolified-iot-controller
Intelligence, Distilled.
This is a Domain Specific Language Model (DSLM) generated by the Smolify Foundry.
It has been synthetically distilled from SOTA reasoning engines into a high-efficiency architecture, optimized for deployment on edge hardware (CPU/NPU) or low-VRAM environments.
📦 Asset Details
- Origin: Smolify Foundry (Job ID:
b8144b78) - Architecture: gemma-3-270m
- Training Method: Proprietary Neural Distillation
- Optimization: 4-bit Quantized / FP16 Mixed
- Dataset: Link to Dataset
🚀 Usage (Inference)
This model is compatible with standard inference backends like vLLM, and Hugging Face Transformers.
# Example: Running your Sovereign Model
from transformers import AutoModelForCausalLM, AutoTokenizer
model_id = "DebMukherjee/smolified-iot-controller"
tokenizer = AutoTokenizer.from_pretrained(model_id)
model = AutoModelForCausalLM.from_pretrained(model_id, device_map="auto")
messages = [
{"role": "system", "content": '''You are an IoT intent parser. Map user commands to valid JSON actions: {"device": string, "state": 0 or 1}. available_devices: [kitchen_light, bedroom_fan, garage_door, ac_unit].'''},
{"role": "user", "content": '''It is freezing, initiate the heating in the ac_unit'''}
]
text = tokenizer.apply_chat_template(
messages,
tokenize = False,
add_generation_prompt = True,
)
if "gemma-3-270m" == "gemma-3-270m":
text = text.removeprefix('<bos>')
from transformers import TextStreamer
_ = model.generate(
**tokenizer(text, return_tensors = "pt").to(model.device),
max_new_tokens = 1000,
temperature = 1.0, top_p = 0.95, top_k = 64,
streamer = TextStreamer(tokenizer, skip_prompt = True),
)
⚖️ License & Ownership
This model weights are a sovereign asset owned by DebMukherjee. Generated via Smolify.ai.
