File size: 2,493 Bytes
63c5c88 e01a7e4 63c5c88 e01a7e4 63c5c88 e01a7e4 63c5c88 e01a7e4 63c5c88 e01a7e4 63c5c88 e01a7e4 | 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 | ---
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-tiny-text-to-code
> **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: `fe9b19bf`)
- **Architecture:** DSLM-Micro (270M Parameter Class)
- **Training Method:** Proprietary Neural Distillation
- **Optimization:** 4-bit Quantized / FP16 Mixed
- **Dataset:** [Link to Dataset](https://huggingface.co/datasets/programmerGodbyte/smolified-tiny-text-to-code)
## 🚀 Usage (Inference)
This model is compatible with standard inference backends like vLLM.
```python
# Example: Running your Sovereign Model
from transformers import AutoModelForCausalLM, AutoTokenizer
model_id = "programmerGodbyte/smolified-tiny-text-to-code"
tokenizer = AutoTokenizer.from_pretrained(model_id)
model = AutoModelForCausalLM.from_pretrained(model_id, device_map="auto")
messages = [
{'role': 'system', 'content': '''The user will provide a natural language description of a programming task. Your goal is to generate correct, runnable Python code that solves the task. Adhere to PEP 8 style guidelines. Include type hints for all functions and variables. The code should be self-contained and ready to run.'''},
{'role': 'user', 'content': '''Create a Python function named `factorial` that calculates the factorial of a non-negative integer. If the input is negative, it should raise a `ValueError`. If the input is 0, it should return 1.'''}
]
text = tokenizer.apply_chat_template(
messages,
tokenize = False,
add_generation_prompt = True,
).removeprefix('<bos>')
from transformers import TextStreamer
_ = model.generate(
**tokenizer(text, return_tensors = "pt").to("cuda"),
max_new_tokens = 1000,
temperature = 1, top_p = 0.95, top_k = 64,
streamer = TextStreamer(tokenizer, skip_prompt = True),
)
```
## ⚖️ License & Ownership
This model weights are a sovereign asset owned by **programmerGodbyte**.
Generated via [Smolify.ai](https://smolify.ai).
[<img src="https://smolify.ai/smolify.gif" width="100"/>](https://smolify.ai)
|