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tags:
- sentinel-manifold
- quantization
- edge-deployment
- int4
- pytorch
license: mit
---
# 🦴 Sentinel Tiny Text — Sentinel-INT4
**Production-ready quantized model for edge deployment.**
This is the Sentinel-INT4 quantized variant of [Sentinel Tiny Text](https://huggingface.co/5dimension/sentinel-tiny-text).
---
## 📊 Quantization Spec (SDM-v1 §4)
| Property | Value |
|----------|-------|
| **Format** | Sentinel-INT4 |
| **Zero-Point (Z)** | C₁ = -0.007994021806 (attracting fixed point) |
| **Scale (S)** | max\|w\| · (1/e) |
| **Compression** | 8× |
| **Size** | ~6.4 MB |
| **Parent model** | [5dimension/sentinel-tiny-text](https://huggingface.co/5dimension/sentinel-tiny-text) |
---
## 🧬 Mathematical Foundation
The Sentinel quantization uses the attracting fixed point C₁ as the zero-point, minimizing rounding noise by clustering weights around the dynamical attractor.
```
Quantization: q = round((w - C₁) / S)
Dequantization: w = q · S + C₁
Where S = max|w| · (1/e)
```
---
## 🚀 Deployment Targets
| Platform | Compatible |
|----------|-----------|
| Mobile (iOS/Android) | ✅ |
| IoT devices | ✅ |
| Microcontrollers (ARM Cortex-M) | ✅ |
| Browser (ONNX/WebGL) | ✅ |
| Edge TPU | ⚠️ (needs conversion) |
---
## 📦 Download
```python
from huggingface_hub import hf_hub_download
# Download quantized weights
weights = hf_hub_download(repo_id="5dimension/sentinel-tiny-text-int4", filename="model_int4.pt")
```
---
## 🔗 Links
- **Parent model**: [5dimension/sentinel-tiny-text](https://huggingface.co/5dimension/sentinel-tiny-text)
- **Main repo**: [sentinel-manifold-discoveries](https://huggingface.co/5dimension/sentinel-manifold-discoveries)
- **Sentinel Hub**: [Interactive demo](https://huggingface.co/spaces/5dimension/sentinel-hub)
---
**License:** MIT | **Edge-ready. Theorem-backed.** 🦴
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