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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-debug-run
> **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: `DEBUG_RETRY`)
- **Architecture:** qwen-3.5-0.8b
- **Training Method:** Proprietary Neural Distillation
- **Optimization:** 4-bit Quantized / FP16 Mixed
- **Dataset:** [Link to Dataset](https://huggingface.co/datasets/smolify/smolified-debug-run)
## 🚀 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 = "smolify/smolified-debug-run"
tokenizer = AutoTokenizer.from_pretrained(model_id)
model = AutoModelForCausalLM.from_pretrained(model_id, device_map="auto")
messages = [
{"role": "system", "content": '''You are a highly intelligent AI.'''},
{"role": "user", "content": '''Can you solve problem number 0?'''}
]
text = tokenizer.apply_chat_template(
messages,
tokenize = False,
add_generation_prompt = True,
)
if "qwen-3.5-0.8b" == "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 **smolify**.
Generated via [Smolify.ai](https://smolify.ai).
[<img src="https://smolify.ai/smolify.gif" width="100"/>](https://smolify.ai)
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