File size: 2,284 Bytes
6470bc7
 
 
 
07e4b33
 
 
 
 
 
 
 
 
 
 
6470bc7
 
07e4b33
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
6470bc7
07e4b33
 
 
 
 
 
 
 
6470bc7
07e4b33
 
 
6470bc7
07e4b33
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
---
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](https://huggingface.co/datasets/DebMukherjee/smolified-iot-controller)

## 🚀 Usage (Inference)
This model is compatible with standard inference backends like vLLM, and Hugging Face Transformers.

```python
# 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](https://smolify.ai).

[<img src="https://smolify.ai/smolify.gif" width="100"/>](https://smolify.ai)